All right, I think I'm all set. Let's start. So, welcome everyone. My name is Rui Adorno, whoa. So, I'm a local from Montreal. I've been living here for almost 11 years now. So, it's one of my greatest accomplishments of my life, like becoming a Canadian citizen. So, yeah, I really love the people here, really love the country. Just the weather at this time of the year starts. It's not so great, but yeah. And I recently, it's been three months now, almost four. I joined NPM, so now I work at the open source team with Darcy, you might have seen his talk yesterday. Yeah, so you can find me at these places and I have, before anything, I have to also thank Joel because I totally just stole his CLI slide, so that little guy there is actually Joel over there. Thank you so much. All right, so we're here today to talk about CLI, right? I hope everyone here loves CLI, right? Quick show of hands. Who uses CLI on a day-to-day basis? Okay, it's off, yeah, okay. It is the right crowd. So, yeah, this is a quick talk and the goal here is just like for people to start, people that are not doing yet, start creating their own common lines, people who maybe are already doing, maybe you learn about a thing or two. So, yeah, let's get to it. Quick overview, so we're gonna go through understanding CLI commands, just a quick basic of how to define a reusable command, how to compose commands using UNIX pipelines, and then add interactivity, like let's sprinkle a little magic on top of it and then go, like, of course, let's use Node.js we did. So, yes, this quick disclaimer, you're about to see a graphic designer by formation giving a talk about the common line interface, which, yeah, and I think it makes a lot of sense. It is a great user interface and there's something that maybe sometimes people don't realize because our very communication is word-based, right? We think in word terms, word they link into things in our minds, right? So, and developers are always looking to reuse things, right? And words are really key words in our minds and we're gonna map them into things we wanna do, right? So, that's what makes the CLI, the command line interface so powerful because basically the commands, they're reusable stuff, right? We love to reuse stuff. And basically, we're storing commands, we're doing our workflow and these commands is just something that, okay, oh, yeah, now I need to do this thing. Oh, yeah, so maybe it's, maybe the command is run, maybe the command is like run my project. It's gonna map to something in your mind, it's gonna make sense to you and it's going to be reusable. So, all right, we're gonna go through a bunch of quick examples. So, very adventurous here, gonna do a lot of live coding stuff, but it's gonna be fun, yeah, it's fun stuff. So, huh, so not gonna jump into node yet. So, quick thing, like basically here, we're gonna use the cat command, basically that prints out contents of a file, right? So, here I'm just going to define, like, okay, I wanna create a new command. It's gonna be full, like for now, it's only gonna be catting things, like just like printing it out. So, that's like step one, the very most basic thing, like defining an alliance is one of the ways to create your own command. In this case, doesn't do much because, well, that's already a building thing. So, but sometimes, you wanna maybe use a variation of a command, right? Command that takes a flag, like, okay, like git status. So, like, git status usually, it's gonna print all this info, right? And let's say you like the s flag, which turns into this more pretty printed things, way of displaying your status of a git repo right now. So, yeah, okay, let's make, okay, status. Okay, that's gonna be my new command, like, I like that thing, like, I wanna be reusing that. So, from now on, every time, okay, now I wanna do status, but the way I like it. So, you basically, like, git status, like, you have that alliance is a new command you can use and reuse. And you can also, like, make it more versatile, like, there is also the function, the bash function way of defining it. So, basically, this one over here, I'm just going to, hey, git status, and then I'm just basically gonna be setting a parameter. So, now I can send down the s flag or some other ones, like, not, yeah, so it's going to do the very same thing that the other one did, right? But, basically, just to showcase the bash functions too, is also something we can do. So, yeah, using node, like, fun thing I did too, like, I just went on NPM real quick, let's find a useful library we could use to do something fun, right? So, basically, in this case, I'm just using some load library, I'm just invoking the node runner itself, and I'm recriting right away, right from bash, that command, and what it does is that, okay, if there is an offensive word there, it returns true, then it's gonna print block. Otherwise, it's just gonna print whatever was it, right? So, let's try it out, that starts to be more fun, right? So, I already, for the sake of, like, making sure it doesn't derail too much, it's already NPM installed. So, let's just create this new command here. So, okay, node, gonna print that, and it's gonna require offensive words, filter. Thank you so much, whoever did this command. And, it's going to take the word as an argument, I'm gonna use that, and then, if it's blocked, which is true, I wanna show anything, and otherwise, let's print whatever was that there, and then I close this thing, and then I close my function. So, let's print safe, oh, hi, yay, there's nothing offensive in this word, it works well. So, let's print safe.  So, yeah, basically just quick demo on how to use a node module, like, even within Bash itself. Yes, so, moving on. Yeah, I think this is an interesting thing, like, took me a while to realize, as a designer, like, I've been learning these things on my own for a long time. So, basically, yeah, and you can also just define any file, any file that is in your path environment variable is going to be available as a command, as long as that file is executable. So, you can even, like, from the local installed modules, like, usually they're not available as a command line, right, even though if they provide command line interfaces, let's say, Joel's thing over there, CLI slides, it is a command line thing, but right now it's not available at all. So, if I go on and just, like, export my path, and I'm gonna contact, like, here I'm concatenating it with whatever was already there, getting my current directory here, and, like, okay, let's get everything that is in node modules bin, that'll be part of the path. So, now, the command slides thing that I have, it's available, it's not gonna work because it takes some other arguments, it's not the point, the point is that, now your internal node module bin, like, whatever local modules we have installed, they're available as a command for this prompt now, like.  It's something I do a lot, yeah. Yes, also, any, yeah, package JSON scripts. This is a super handy way of, like, just project base. I know, here's, the crowd is most node.js, so probably you all know this one already, but it's a mandatory one I had to mention, right? So, in your package JSON, you can define scripts, and those scripts, they can be run anytime later. So, NPM run, you can NPM run, hello, as long as hello is available as a script for that package JSON, it is going to run, you can reuse, a handy thing is that, this way you can even reuse CLI tools that are local to that project, without having to do the path thing, like NPM does it for yourself, basically. So, package JSON also supports the bin property, so basically this allows you, this is what we know the publisher, the maintainers of module, that's what we use when we want to distribute command line tools on NPM, right? Then people can just NPM install it and conveniently reuse it. So, I tend to try to share all the things that I do when I find it a little bit useful, I'm going to make it a quick node module, push to NPM, then myself I'll be reinstalling that later, whenever I switch computers, whenever something happens, and other people can reuse, right? You can share to your coworkers, oh yeah, I have a script for that, just NPM install this thing, it's going to do it. So, and here we get to the composing commands, yeah, which is the powerful thing about Unix, like the idea, Unix has this idea where every command is its own thing, and it tries to be like really specific, some of them are really not, like some of them get really busy with all the kinds of arguments and powerful things it does, but the idea is that you're gonna run LAS, it's going to list the files that are in that folder, right? You're gonna run cat, it's going to print the contents of that file, so you can actually combine those together and start creating like, okay, now I'm creating my own stuff, I'm reusing the basic commands that are available, you might be reusing some other commands that you installed from some other open source projects, and you can be combining them together and create your own workflow, and you can share it to people. So, basically yeah, a couple more examples, and this is where things start to get more risky because this might fail, anyhow, let me see, yeah, I think last time I had to delete this one. So, let's just say find, find is a command that allows you to list all the files, it's going to be recursively traversing all the folders and printing all the files, and you can specify arguments to start filtering out, like in this case, I'm filtering, okay, just files that has the name that ends in .js, so it's going to print all the files, oh, surprise, there's a lot of .js files in my node modules. So, let's say, okay, I want to get word file, I think I make sense of a command that I can reuse later where I could like, oh, let's get all these files, and then I want to grab, grab is one very handy command that allows you to filter items, so in this case, yeah, I want to, I want to be able to just like filter out one of these, so get word file, it's going to traverse all these files, and I want to just like, oh, just give me the ones that has CLI on it, so you see the other one is gone, and if I just, okay, no, actually just word, so all the CLI stuff is gone, it just prints the one that has words word on it, which is offensive word filter there, so this is like very basic first example of using the UNIX pipeline, right? So, the idea here is basically like the pipelines, you're combining the output coming from a command and to the second command, right? So this is, it kinds of connecting pipelines, and then the stream of information flows through them, and this is like, this is the origins of the stream library in module in Node.js, which I always had a hard time with, and I wish I didn't miss the other talk from Mateo about it, but anyways, so all these concepts could actually come from the UNIX pipelines, where you can connect the commands together, right? So, XR is handy utility that helps out because when you're connecting those pipelines, you're connecting the standard output into the input of the next one, so when you have a command like cat that wants to receive an argument, XR is going to help you out, it's going to, okay, okay, not connecting the standard input, I'm gonna read that thing as an argument. So in this case, let's make another handy command, print file. So, again, the same recite we had last time with the name and filter in JS, then let's just select one, so basically continue from the idea of the last command, but this time let's print the contents of the file with just select, right? So, print file, and okay, I want that word file again, but this time, print it, ah, it failed. Yeah, not going to debug that one, but let's just do it this way. I'm gonna do it manually because I probably just got something wrong here, and I'm just gonna manually, like instead of using the argument, I'm just gonna hard type the word here, where the argument usually goes, and let's cat that, and there you go. Like my word file, like I can see that that module is actually very simple, very simple, it's just like reading from a term to block JSON, and like, and it does the logic, oh yeah, should I, does it match anything in there, return true, otherwise false. Oh no, what happened? Oh no, is it rebooting? It was going wow. Okay, oh good, oh good. Let me move on. Yes, so, continue. Yes, you can also write down files from the pipelines, they have more operators, and this is the only one I'm gonna be showcasing, like basically the greater than sign, or smaller than, anyways. It's going to get that stream and dump it into a file. So like very handy too, in this case, oh yeah, this is a fun one, yeah. So let me get back my demo.js. Yeah, so basically this one, let's build a command that's going to, okay, print out from the file I'm gonna send in, and then it's going to replace anything like sad, SED, I call it sad, not sure, probably not the right way to call it. It is going to replace things, like in place, so it's basically just a string replacement, right? So I'm going to swap log for error in any of the stream of data that's flowing through here. And number two is going to be the second argument of my command, so I'm gonna save it, write it to a second file. So let just quick show what's going on here. Demo.js is basically doing the same thing that other command was doing using the library, but this time is a JavaScript file itself. So it's just console log. So what I want with this is just, okay, let's replace log with error for any file that I send into this thing. So make error, and I send in demo.js, and okay, and I wanna save an error.js from that. So I run it, and now I can see error.js has the same thing, but replace log with error. So basically showcasing the writing to a file operator using the greater than operator and multiple arguments with the number two there. So yes, I hope we have seen the light. Like, okay, okay, this is good. This is good, I can actually reuse this. It's not rocket science, right? Hopefully you're all good to go, like composing new workflows from the basic Unix commands that you already know. And then you're probably gonna be interested in learning about some other more, like because the more you know, the more commands you start learning about, the more ideas you're gonna have, oh yeah, this can actually be automated like that because it could use that other tool that I just learned about, yeah. So, and I like to introduce like a very, very cool handy feature, basically a Unix command that just allows you to turn any of this stream input, like into interactive interfaces. So you can like just build things that are gonna turn into interactive lists and you can select one and you can do whatever you want with the output of that stream. So yeah, basically, I call it I pipe to, the interactive pipe to thing, but the command is IPT. So given any list in the shell, you can like, okay, listen to files there. So I can pipe that list of files into I pipe to and it's going to be the interactive interface of it. Oh, nice. And then I can just like select one and what it does is just prints whatever you select. So it's going to allow you to connect that to some other stuff. Then you can start creating really handy work flows right with that. So in this case, yeah, I've just selecting, oh yeah, I have this other handy command here that, okay. Let me just like interactively, oh nice, oh cool, cozy mood. Oh no, what is going on? Anyway, so yeah, you're used to like CD, like in order to navigate, but it would be handy if you could just like, oh yeah, now I can see the list of files. I can just like select the folder in it and like, oh yeah, it's kind of cool. Very basic, just like showcase some examples. Another, yeah, another very basic one. You can have like a list of branch for a git, git also like because it has so many lists, right? It has lists of branches, lists of comments, lists of remote repos you might point into.  Okay, let me connect the list of branch, then I pipe that into the interactive thing and then I can like, whoa, why not? I can check out into a different branch, right? So yeah, okay, yeah, I didn't check out, but like in this case it failed because I had some modified files, but you can get the idea. And yeah, it has some handy options too, like in this case, I have this command for printing files and it's going to be listing all the files in the folder and I'm gonna use this multiple argument, dash m, that is going to allow me to select multiple items on that list. So instead of being just like selecting one, it's going to be like more like filtering out the unselected files. So, oh yeah, let's print all of the things that I selected in there. So print files is going to show me a handy list. There is now a checkbox sort of and I can go and like, oh yeah, let's select the demo and the error and it's gonna pipe that info into cat that is going to print both of them and we've seen that earlier and you can see this is the same thing. So handling file names, basically, it also has like this very handy thing when you're dealing with get that when you're doing like get status, in this case that same fancy view with the notification in there like showcasing the status for each file, right? I'm gonna use this handy dash p option that is going to just try to parse the file path out of the item itself so that I get rid of like the d's and m's and question marks so that I can actually reuse that path right away and I can like, I can just print the info for that one. So as you can see, the list still has the metadata in the beginning but as soon as I select one, the next command works because the dash p command like get rid of all the things that are not part of the file path there, the file name. Yeah, and the last thing to showcase is the fuzzy finder auto complete mode. So basically I can like, you know, I'm also going to take out the opportunity here to show that you can also send in as a file name. So like I can like, send in just IPT and like the package JSON. So it's going to explode like the file into mode, like for each line is going to become an item. And then the argument is actually dash a, this is wrong in the slider. Sorry about it. But then it's just like, it's just going to filter out basic, based on what you're typing like an auto complete kind of thing. You can like, oh, description. So, oh yeah, setting that line. So we're gonna output this. So yeah, all crazy ways to like, do cool commands, like interactive commands with it. Just throwing out like a real quick thing I put together for the demo. How many of you know about the Pocoche CLI? Like it was recently released as a known CLI. So basically it's one of the NPM internals. So allows you to like get fetch metadata, fetch maybe just like the tar ball, but not NPM installing everything that goes with it. So basically I did like this NPM install version command here that is going to use a metadata from the NPM to basically build a list of all the versions, list them. And when you select one is going to NPM install that exact version. So real quick, NIV. And then I'm gonna NPM install. In this case over here, I'm kind of hard coding the name of the package, but the idea is kind of argument. And then gonna be sending it into node because I wanna be able to parse that metadata to retrieve just the result of that Pocoche call and that thing over there. Yes. I'm gonna get only the versions. And then I'm going to turn this into a string. And then I'm going to pipe that into IPT. This one is too complicated. I should have saved it for this. But anyways, let me showcase like Pocoche Pacument what it's going to do. Then you're gonna get the idea of it. So basically I'm fetching the metadata for a specific package. In this case, I pipe to itself. Then I can get like a list of versions. Oh no, I didn't touch anything. And I was about to demo the cool NPM stuff. Oh, what do I do? Oh, it's coming. Yeah. Okay. You just need to walk in. Yeah, yeah. Thank you. So yes. So basically over here, I'm going to filter just the versions. So what I was doing with it is that I was going to use node here real quick to just like get the keys of the version names, of the version there so that becomes more usable. Yeah, so I have a list of all the versions. So this list, what I was doing after that was like concatenating them, like making them a string of like, just like we had the LS in other commands, right? And those I can like pipe into I pipe to and then we can select one. And then with that selected one, I can just like pipe that into NPM install and do like the name of the thing at that result. That thing is not, don't think it's gonna work. I had to do that all that other complex crazy way like this. And then like this. And then I could like NPM install and then module name at specific version. So NPM install 1.0. Woo. So yes, interactive commands are fun. And as the last one I wanted to showcase is the no-test list is when I start digging into these, like sometimes it gets out of hand. So this one became like a kind of larger project. Like there's a lot of interest from the community, people that just jumped in and start contributing more. So it became kind of like larger package because it has like many features around it. It's just not the basic thing for my pipe to, but it uses I pipe to provide the same interface, right? So basically NGL is going to list all the scripts you have in that package JSON. And once you select any of them, you just hit enter, it runs. So that's the basic idea of it, right? At that point it's just like the basic I pipe to kind of thing, but then it does all sort of thing. Like in this comes from the community contributions like keep track of the last run command. So then you run it again, like it's already selected, right? Super handy if you're like using it day to day basis. And also if you're just like, if you're just maybe it's a task you're running all the time then you can remove the L so it's not no task list, it's just run the no task. Like it just runs the latest ones so you can just like be running them again. And whatever you want to switch, you can like go back to the L, you can select multiple items. So like, okay, let's run both of them. Like same thing with the multiple, you still have them selected by default. So yeah, yeah, it's also available on NPM. You can NPM install NTL, NPM install I5 too. Yeah, and I hope you all feel really confident about creating all these workflows. I'm gonna make sure these lights are available so that you can use as a reference to start creating your own, right? Yeah, so thank you very much. Yeah.


Okay, we're back live here at the Stanford, Excel symposium at the end of the day, and this is theCUBE, our flagship program. We're out to the events, extract the ceiling from the noise, and I'm John Furrier, the founder of SiliconANGLE.com. I'm here with Jeff Kelly, on boogiebond.org, and we're here with Madhu Sadkuhar, who's the founder of Cetus. It was sold to VMware to spun out the Pivotal, all the way to theCUBE. Get a little closer to the microphone, so we don't get the background noise there. Thank you, John, and thank you, Jeff. So the story on your company is we've been following your great success, because you guys were doing some pretty compelling work in social data, in Palo Alto, right on University Avenue, True Ventures Finance, a great, great company. You guys had a nice run, but clearly you didn't even break out. VMware saw you guys and brought you in on an acquisition. Give us the update on the company's role within VMware. Obviously Pivotal's, the high profile spin out, I had a post on it, Dave Vellante had a post on it, so EMC, VMware spun out Pivotal. Cetus, Green Plum, Spring. Gemfire. Gemfire, yeah, so give us the low down. Sure, and thanks for talking to me today, John. I mean, you've been a good friend for us, and you write good articles for us on Pivotal, so thank you. So with that, I think, what can I tell you? I think right now my role is playing the, what I call, I run Pivotal Analytics for Pivotal, and Pivotal Analytics includes the Cetus, as you mentioned about, and it encompasses from Hadoop Analytics and top of Pivotal HD, to streaming analytics. To the point, we actually do also Cloud Foundry Analytics. The way in which we are seeing the vision of the company now is going forward. Lot of our customers want to build applications on Cloud Foundry, our spring environment, and they actually want analytics to be available. I think where you see the next evolution is, as you build the mobile apps, you have a choice. Would you want to go build it in a platform where there's no big data paradigms and data structures available, or would you like to come to a place where all these are available to build the next generation mobile apps, where you have enabled streaming and Hadoop Analytics available. So we want people to come to Cloud Foundry. We want to make analytics as a core reason why they should come there. And that's a big bet we are making. So talk about the now the mashup of the Cloud Foundry, because that's important. I mean, Paul Moritz set out his vision when he was the CEO of VMware in 2010. We were there as our first year doing theCUBE. This is going to be our fourth VM world coming up. It was the mainframe, the software operating system, and at the top of the stack he had applications. Now, the world's changed, big data became very fast growing market. Those apps kind of didn't materialize as fast enough.  Microsoft, that's his background. Gelsinger is an infrastructure guy, so great team. So we've always been pro-pat and pro-Paul. So talk about- Ingen Yang. I said Ingen Yang. Yeah, and Ying and Yang, and these guys, that's the Wintel, we called it, of Cloud and all the social. But now Pivotal seems to have a rebirth freedom, right? Because now there is a developer focus, you have the Cloud, there is Spring there. There's nice separation between the two. What is the strategy with data?  How does your piece fit into Cloud Foundry Spring? Explain that. Yeah, it's a good question. I think for all the people, very few people can describe as good as you have done, so thank you. But I think you've got the picture. I think what I think Paul's vision is, underneath he wants to have a Cloud infrastructure. There are Cloud orchestration layer. So that includes Bosch. That includes how do I launch these instances, manage the instances, in terms of dynamic resource orchestration, in terms of provisioning, in terms of configuration. That's underneath Cloud. And the Cloud needs to be hybrid Cloud, in his vision. So we support Amazon. Like today, Pivotal and Ingen still does Amazon. We want to do that on VMware. We also, in the future, we want to support OpenStack. So we want to be neutral to the type of Cloud. And we want to provide a Cloud orchestration layer. On top of that, we want to provide the best in class, what we call all-in Hadoop, which is Pivotal Hadoop. The goal of Pivotal Hadoop is, the reason for you to run Hadoop with us would be the best performance, best scale, and also be able to provide all the services that you need on Hadoop. So that's what we call Pivotal Hadoop. And on top of Pivotal Hadoop is where Pivotal Analytics comes in. And Pivotal Analytics is where you can do real-time streaming data. You can do aggregation. You can do event analytics. You can do behavioral analytics. To the point, you can do modeling. So the reason people do come to Pivotal Analytics should be of many reasons. And we want all of that to be available on the Cloud Foundry infrastructure. So once people come to Spring in Cloud Foundry, you have access to them, all the APIs, SDKs, and libraries for them to build best-in-class application which can use big data services underneath. So that's kind of the view we are doing it. And I think it's an incredible journey of all the assets that Paul pulled together. I'm humbled to be part of this journey. And I would say lucky and thankful for them to be selected in this process. And I'm very happy with them. Congratulations on your successful entrepreneurial journey. We have to get the hook here because our next guest is here. We want to squeeze you in because you're a friend and we're a big admirer of your work at Cetus and now in VMware and now Pivotal. We're obviously following it. I have been positive on Pivotal but I'm not all there yet. I'm still serving judgment. I did slam the CRN article that said compared Paul Moritz to Jeff Bezos which I thought was a little bit over the top. But I think Moritz has got the chops. He's a tools guy. I think he's going to do very well with Pivotal. Right, I think it's also worth pointing out the investment by GE and how that's going to play. I'm curious. I know we don't have a lot of time but I wanted to get one question if I could. The whole concept of the industrial internet and how that fits into your strategy or is that really the underlying area or focus area that you want to provide these capabilities for bringing together that kind of machine generated data? I think if you think of it, I see the data in multiple ways. There's a data that's called, what I call data has certain dimensions and time is an important dimension. We call this time series data. Industrial internet will generate telemetry data as Paul calls it, time series data. The main thing we want to build analytics is should be able to handle a simple good old reporting, clickstream data for all the web and social companies to the industrial internet companies or the applicants will generate sensor data, telemetry data, which has time series in nature. We think that will generate an order of magnitude more data and need have different type of analytics and that requires different type of data structured analytics and we want to take a bet with them. Yeah, it's a very much, you've got to orchestrate a very, it's a very complex environment when you've got, you know, you've got different workload demands when you're talking in an industrial internet scenario. You've got some real time, you've got some already doing more batch analytics to inform some of that real time. So it'll be very interesting to see how that plays out and I think it's a very interesting, I guess it's an investment and a partnership to be doing some research and development with the, you know, is now kind of a, you know, they're a manufacturer of industrial equipment and now they're also in the, really the software and analytics business has applied to that equipment. So it'll be very interesting to watch and, you know, like John, I'm very interested to see how it goes. Yeah, we'd love you guys, great job. Exciting to see the competition. Obviously a lot of people are making these big moves and getting the GE endorsement of the Brazilian music killers. Congratulations. Okay, we'll be back with our next guest here. Exclusive coverage from the Stanford XL Partners Symposium live from Stanford University in Stanford, California. I'm John Furby, right back with our next guest at the short break. Thank you John.


righty, we have some interesting news coming out of Carowinds today. Interesting in the aspect of it's not confirmed yet. Hopefully I'll be able to grab an answer for you guys if it's confirmed. I'm going to reach out and try and figure out what's going on with this 2019 park map that Carowinds teased on their Facebook post today. So they did a 2009 versus 2019 map comparison and lo and behold, the Rapids ride is not on the map. Again, it is not confirmed yet, but it missing from the 2019 map does say a lot. So we know it's missing from the map. It could be a couple of things. It could be upgrades are maybe gonna happen. So maybe they'll actually upgrade the roaring Rapids attraction like they're doing over at Not Sparey Farm or maybe it'll be removed. Who knows? Honestly, comment down below what you think throughout the video because I'm gonna put forward a few kind of theories I have about what's going on. This is gonna be a really interesting video, especially if your home park is Carowinds. Cedar Fair is definitely heading down a road of doing interesting ride removals or upgrades and I can't wait to see what it is. So again, it doesn't necessarily mean it's gonna be removed. So please take whatever is said in this video with a huge grain of salt. I don't have any inside information about Carowinds nor this attraction. We're just assuming it's gone for the season or being removed because of the 2019 park map. So Cedar Fair has definitely been removing rides. We've seen Orbiter Go. We're seeing other attractions that other parks being removed as well. And you're seeing attractions over at Not Sparey Farm being upgraded similar to this. And now you're seeing this ride removal or ride upgrade in the 2019 season. So very interesting. Now the only thing I don't think, the only reason I don't think this is a ride upgrade is because they could have done that during the off season at the end of the season.  I think like a couple years ago or whatever that ride was removed, we received their excess boats. I do know Canada's Wonderland actually received more parts for Whitewater Canyon recently, our River Rapids ride. So that would align with it being removed. Again, take that with a huge grain of salt. But I do know Wonderland does receive parts for their water rides from Carowinds from what I've seen. And I know that if you were there during this season at Canada's Wonderland, you could see under Dragonflyer WC seatbacks, Whitewater Canyon. It was WWC seatbacks in a giant crate. So that would make sense. And I know that there's more arriving. So it does all align that this would be a ride removal. So again, my prediction is this ride is being removed for something down the line. This doesn't mean 2020.  I have a feeling that if it's 2020, it's going to be something else. If it's 2021 or later, it's going to be a coaster. So Carowinds is definitely not investing in a coaster anytime soon. We know that from the stockholders call, we know that from a news interview they did online. Carowinds is now focusing on other things to invest in. Again, that's probably just the two to three year mark that they're talking about. So I'll go into which years I think a coaster could be coming to Carowinds. But it definitely seems like Cedar Fair is heading down this road of not building roller coasters every three years, like they've been doing at some of their parks. So it's more going to be like five every five years, your park will receive a coaster. So keep that in mind whenever you're predicting a coaster for your park, unless your park is under an expansion plan. So Carowinds was under an expansion plan, but they are not. That expansion is over. And Canada's Wonderland is now under an expansion plan. I'm assuming Nottsbury Farm is under an expansion plan. Cedar Point's always under an expansion plan rolling of the eyes. I'm kidding. I'm just jealous. And CGA will be entering an expansion plan shortly. I actually know a little more about the CGA expansion plan because they said they're going to mimic kind of what they did over at Carowinds and improve that expansion plan that they did and the way they did it over at CGA, but in a longer timeline. So that's a little interesting, that wording that was used in the interview. So CGA is definitely going to be heading down an expansion plan.  So what do I think could be the coaster timeline? Well, I'm looking at 2021 at the earliest. And the only reason I'm saying 2021 is I'm seeing signs that Canada's Wonderland may potentially be getting a coaster in 2021 as well part of their expansion plan. And there's sister parks with Carowinds. So it'll be interesting. It is a little early. And I may not necessarily believe that Carowinds is getting a coaster in 2021. But I do have reason to believe Canada's Wonderland is getting a coaster in 2021. We'll actually have a video on that soon. So I'm looking at more 2022 2023. I definitely think it's going to be one of the three years so 2021 2022 or 2023 that they're going to get a coaster and it's definitely going to be in that plot of land looking at the map looking at Google images. That area definitely looks like it's going to house a coaster. Don't know why the ride was removed so early. But who knows. So again, they're sister parks with Canada's Wonderland. So whatever Canada's Wonderland does and whatever Carowinds do, I honestly think they'll eventually mirror it or upgrade upon that. So that does lead me to the types of coaster that I coasters that I do think Carowinds will receive down the road. And it's definitely interesting topic of discussion. So again, Carowinds and Canada's Wonderland are very close parks and they definitely build a lot of similar attractions. Usually Canada's Wonderland builds the attraction and then Carowinds kind of does it afterwards. So we're now seeing the two parks build different attractions for the first time in a while. And I honestly think they're going to kind of like reverse those attractions if that makes sense kind of spoiling my future videos. But oh well, it kind of needs to be set in this video for my point to get across. So yes, the Carowinds expansion is over. Yes, they're focusing on different aspects of the park. I'm assuming water park kids area and family attractions for one to two or three years, and then they'll get another coaster. This park is now becoming a super important park for the chain. So I wouldn't be surprised to see every three years to five years, they're still getting some sort of coaster or bigger attraction if that now a bigger attraction could mean something like forbidden frontier as well. The chain is heading down this direction of building kind of experiences. But I definitely think dinosaurs alive will be that plot of land they use that experience for if they're to put one in over at Carowinds. So what do I honestly think the next coaster is going to be? Well, I have two models in my mind. A wing coaster is one of them. I think a wing coaster at Carowinds would do phenomenal. I don't think there's one in Florida. I'm trying to think really hard sometimes I always forget again, I'm not a hardcore enthusiast anyone that watches my channel knows that I am definitely one of those kind of like hardcore enthusiasts mixed with a little bit of GP so I do get my facts wrong and stuff like that. Again, I am always open to criticism in the comment section down below or correcting me in a polite way always feel free I'm open to learning. But I don't think there's a wing coaster in Florida. So I think a wing coaster at Carowinds would actually do phenomenal and draw people in from a broader audience. And I think that's something we could potentially see over at Carowinds now whether it's a launch or a lift hill, I definitely think it would probably be a launch because it looks like it would be next to fury and a lift hill would look a little weird next to a giant lift hill. So a launch coaster would do a lot better in that plot of land than that. Now I do honestly think that a dive coaster is more likely. I don't know how big the plot of land is based off of the map and again maps tend to make things look smaller. It looks like a pretty hefty plot of land. So I do think that it's big enough to house any one of these coasters. But I do think a dive coaster is most likely again this goes back to Carowinds and Canada's Wonderland being sister parks. So this is where it gets really interesting. Will Carowinds build a dive coaster and break Canada's Wonderlands records on the dive coaster? And then will Canada's Wonderland build a mock double launch coaster and break their records on that? Honestly, that like to me that screams yes. I think that's the most plausible thing to happen and a dive coaster in that area would pull people as well, especially if they're going for world records. You would have people coming from Florida and neighboring areas. Other theme parks around them don't have any attractions like that. I know Bush Gardens Tampa has a dive coaster, but it is outdated, even though it's an amazing dive coaster still, but definitely room to improve upon that. So what do you guys honestly think could be coming to Carowinds in 2021, 2022 or 2023? Or what do you think is happening to the Roaring Rapids ride? It's definitely a very interesting topic of discussion. Definitely I'm going to be reading the comments down below on what you think can be coming. Do you think it's going to be a wing coaster? Do you think it's going to be a dive coaster? Do you think it's going to be a completely different coaster? Definitely disagree with me down below if you think these two options are not up for discussion whatsoever. Definitely want to see anyone's opinions on the matter. But hopefully you guys really enjoyed this video on Carowinds and what I think is going to be going on with the Roaring Rapids ride and in their future. Thanks for watching guys. Don't forget to hit that like button, subscribe if you haven't, and share this video for others to enjoy. Have a good one guys. Bye.


If you a what's good boys you knew this one was gonna be my favorite I'm so excited to get at the NFC north my boy Avery did an incredible job building this team. So Avery dude I love you. Thank you so much. I appreciate it a great mix of all the players honestly on this squad Although there's not a lot of bears on offense, which I also don't think is that surprising because Packers Lions and Vikings combined for some insane Offensive players over the years So we got boxy our Elting Jenkins Frank Ragnall Kyle Long and Tyrell Crosby get TJ Hawkins in a tight end Jimmy Graham your Michael Finley. We got Megatron, of course gold 99 gold 99 Devonte Adams Randy Moss 98 Devin Hester 94 and then 96 Justin Jefferson Dalvin cook my boy at halfback Barry Sanders as well And then of course the MVP Aaron Rogers 99 at quarterback with fourth quarter Mitch at the back up Also, I'm starting to run out of light here in Hawaii So if we lose light in this video just and fly up, but the Bears make a little comeback on defense We get Dran Harman. We got Colo Mack for Spielman Blake Martinez Jamie Collins Kyle Fuller 99 It's I would feel Charles with the gyros under Casey. Hey, we're this team is so good a 98 overall We're literally so close to 99 the only reason it's not a 99 left and right tackle center left guard We're like that close to a straight 99 overall team.  Thank you so much We're starting to clean these up boys So the squads that I'm still looking for if any of you have a team like this or want to build one for a video That'd be amazing. So so far we've already done the AFC East now the NFC north the AFC north and the NFC East So that is four for eight if you have any of the other squads or want to build one Please shoot me a demo on Twitter. That'd be amazing either way Let's hop into this one every two and two in a season right now So hopefully I can pick them up a dub right here. Hey, he's even got the lion's unis on for me This guy knows let's get it Sam Mills Mike Evans Chris got Buck in your steam team Buck in your steam team Don't ask any questions. It is it is. Oh, we do have Devin Hester return man though. Oh Okay, so we've got hot row master Gunslinger quick draw Betsy scrambler Rogers reach for it recuperation Energizer and then Hawkinson's got some abilities to Let's try to hit Hawkinson if he's there Mmm, I need it to wait wait come down. No, that's bad. That's bad What is that animation? Oh, I guess it's Mike. It's golden ticket Mike Evans corner I guess I understand there is a small window of time Where I finally was not throwing interceptions on the first drive But now I'm back now. I'm back to throwing interceptions as soon as I start games Ooh throws in the middle of the field gets hit hard. Who is the quarterback? Another big hit, but he's just having his way right now. I'm trying to figure out who the quarterback is Doug Williams is the quarterback here He's gonna throw underneath. We are hitting. All right, Duran Harmon. You got to get there. This is a run. Oh It's not this is bad, and I'm blitzing. Oh, okay. Okay. He didn't get anything I literally took my free safety out of that play. He definitely had a touchdown. This will be the run Yep, that's the run. Yup. Let's go got Barry Sanders on the Buccaneers team team interesting Oh, that was so close to interception. This is a red zone stop though He's got a field goal this fourth and nine great stop boys. All right. Let's get cooking boys He's got Vita Vaya. Nodomica and Sue inside stuff Vita. That's two inside stuffs Let me just show you how broken this is. Oh, I was gonna run it just to show you guys how I couldn't run it But it worked Barry over the middle just barely is gonna pick up seven. Oh We got time boys We got time to think all that's best interference doesn't matter Randy Moss has got it Did he cracked or any moss in the middle of that play? All right, Justin Jefferson? Oh Golden ticket Mike Evans wanted that but he could not get to it second and four clean oh Hockinsons got him Dusted dusted. Oh, I should have stiff arms. Did I literally just have to throw my interception right at the start? Get it out of my system. Then I play great football. Yup.  I had once okay, and Barry has so much room. Let's go pull back fake hat-back flip Dude, I don't think I've scored with this play yet this year, but I want to so bad, but come on, baby Come on, baby. It's so bad. It's so bad. All right. I cannot fumble the back here. Let's go Let's go with this. Yep. Yep. Hold those blocks. Who? Who are you blocking? Is that hot consider Jimmy Graham? Who are you blocking? There's nobody over there? All right, we're going to the side of Megatron on a half back stretch Delvin Cook is gonna walk in. Delvin Cook in the Bear Zuni is gonna walk in. We're going for two.  I need that interception with the fridge, bro I almost made it with William Perry. I'll play you underneath He is going for it ladies and gentlemen. Let's see what he tries See what he wants to do here. Oh that corner routes open that middle is open too. There's a lot open I'm blitzing Kalomak and Fuller No, I have to be able to pick that off. No, I knew he was gonna do that too.   That was very field goal range right there. He just booth field goal range right there I'm so mad. I Want to get to the quarterback, bro. Is this tight end up the left side gonna go out for a route? Okay. Yeah Yeah, let's go Zidarius Smith big time third and 18 Zidarius Smith a big play down the cooks had some big plays berries Had some big plays all squads going off right now No way that is ugly, but if it gets the job done, I guess I don't judge. Oh No way that is high key. So trash. He's running chew clock. As long as he doesn't get a touchdown. I guess I don't care Got a successful spin move all year Oh, I might just have to tick-tock that one baby. Is there any reason I go for two here? No, the only reason I go for two is that a pure disrespect. We're lobbing this to Megatron. Oh Passing ferrets as mad passing ferrets.  Oh That is an interception waiting to happen first to ten. I don't know what he's looking for here Let's put this game away. Let's see what this looks like. Oh, is that open? Megatron Megatron with a huge catch great throw from Rogers making some redemption here And now we can choose some clock. I'm gonna run that fake peak zone bubble basically It's only half a peak zone bubble, but this is all that I can work with in Madden 21. I will take it though Oh, oh Dude sometimes inside stuff literally works against you like Vita bag got upfield so fast that he couldn't make the play I'm gonna run the exact same thing. I just didn't touch that. Why am I chewing clock?  I think he dropped everybody to coverage.  I think he'll still be able to do it I'm gonna go the field goal here because even if he scores I can kick another one 16 to 10 Oh boy, I'm nervous now second and four. This is an intense game of Madden right here I gotta show up for my NFC North boys. Oh Okay, well as long as he goes out of bounds, I don't even care if he scores a touchdown I almost want to let him score a touchdown if he doesn't realize the clock management All right, let's put Collins over there get him ready for that underneath dude. Why is that keep getting so open? It's keeping the clock not moving though because he keeps going out of bounds. I kind of like it This do I decline it? Yeah, I'm giving him a touchdown.  I do know how to beat it. I've hardly pulled this out yet today Let's take that clock boys He's gonna ice me. I've got focus kicker I do not want focus kicker for a game winner, but I don't really have a choice with two seconds on the clock He should call time out to ice me or he's just accepted his fate IQ is exploding literally the smartest man alive with the NFC North squad I am telling you that that decline was the smartest play of my life. Oh, let's go Well, it's super super super heat banger. I hope you guys enjoyed it Hey, the lighting stuck with us for the whole video side stuff. I will see you guys in the next video Thank you for watching always just a banger. I loved recording this one. I'll see you in the next video. Peace


Before I start the second lecture, I will like to share with you some of my personal experiences in some of the aspects that he mentions about communication in general. But more importantly the fact is that he while he is talking about this in the context of research, you will all agree that all of it is important for every teacher who teaches any subject. I realized pretty early in life, when I joined as a teacher that we are not taught at all how to teach. It is presumed that if you are appointed as a lecturer or a student professor, you are able to teach. If you have done a postgraduate degree or PhD, you are able to teach. This is nonsense. The only people who are taught how to teach are actually school teachers who are required to do BA ed and something like. We do not have BA ed means Bachelor of Engineering Education. But you will agree that something of that sort is essential because something which you are going to do for 40 years should all of us be compelled to discover good teaching methods only as we go along. Meaning that first 3, 4, 5 years of our life what we teach is perhaps not as effective as it could have been. So, this is something which is now getting corrected by AICT. Remember I mentioned that research methodologies is one of the core courses that is being made compulsory across all postgraduate programs in engineering. Communication and ethics is another core course which is being made compulsory. Sadly, however the communication course that exists even in IIT Bombay has not been very effective so far because it is traditionally taught by the humanities department and communication is not a course which you can study while listening to lectures. It involves lot of practice whether it is oral or written communication and so on. I will tell you my own experience when I became a teacher and I felt that I must improve my teaching. I did 2 things which helped me tremendously. I am talking about 1973, 74. I purchased a tape recorder. In fact, I remember a big fight with my wife because the tape recorder that time costed 750 rupees and my salary was a grand 350 rupees per month. So, I would have wives of course would love saris or some such useful things in life. In fact, first she thought I have brought it for her to listen to music and then she found out that in the night I was standing in before the mirror and was giving a lecture to myself. In fact, now I realize that my neighbors must have called me a mad fellow that type as he mentioned. I did not realize but I tell you when I replayed that lecture I thought that I was quite fluent but when I replayed that lecture I noticed several who break wrong choice of words etcetera. I did that consistently almost for a month. It helped me to improve my skills. The second thing I did is I selected some colleague teachers each one of whom was known for a specific attribute. For example professor Lemay used to be famous for his time management. So, he would start with a lecture in the morning as a maths professor some theorem let us say at 8.30 sharp and at 9.25 sharp he would have written QED. Nothing artificial about it. The lecture is free flow there is lot of interaction. There is perfect time management. There is a senior teacher of ours Professor Bedford who was well known for extremely decent handling of the participating students.  But the way professor Bedford very patiently replied you have a point. However, if you once again look at that point from this point of when he spent three minutes laboriously explaining. I did not react at that time, but later on when I became a teacher and I was attending his class primarily to understand how he can maintain that patience.  He told me something which is very vital I will never forget in my life.  The question is genuinely in the minds of that person that is why that person is saying this question.  A very important lesson for a teacher. So, these are the things which although we will be speaking in the context of research methodologies you will agree that it should benefit all ten thousand teachers in terms of improving their teaching as well. He talked about humor. So, let me end this monologue by my own experience of humor. When I was studying my bachelor's in J. S. I. T. S. in though this is 65 I think 65, 1966, 1965, 1966. There was a very renowned professor of Mathematics Professor Paria who used to teach us maths. In spite of being extremely knowledgeable his lectures were completely drab. He would write down theorem and prove and very systematic voice, but completely drab. The lectures used to be boring. One day he came he wrote the theorem there and then suddenly stopped and they turn to us and says, now I will tell you a joke. So, suddenly there was a furrow because Professor Paria telling us a joke and then he says in a very monotonous voice exactly how he describes the theorem he says a table has four legs a cow has four legs therefore table is a cow. And then he turned back now we will solve this theorem. That is the funniest kind of humor we had heard. We did not know whether to laugh or whatever, whatever, whatever. Three or four days later we had another professor Kaili of English who used to help us prepare for our debates intercollegiate debates and I was in the debating team and I was reciting this very humorous incidence to some other colleague members of the team and Professor Kaili was listening to this. And then he said oh Paria did this. We all looked at him. He says you know Professor Paria came to me last week and asked me my lectures are not getting interesting. So, what should I do? And I told him tell a few jokes. So, you see the notion of humor itself has to be understood and imbibed properly. It can be done. Believe me I mean that professor was so around and he was a great maths professor and there is absolutely no lack of any intellectual capability to understand it. But it simply so happens that he never in his life gave importance to these aspects. He thought that he is dealing with maths and that is good. So, anyway life is very interesting and we should attempt to make it more interesting to our students who all the teachers. There are a total of 12 lectures which we have given here. Each one of them is actually important. Unfortunately, we may not have time in the mega workshop to conduct all the lectures. By the way all these lectures even in those days when I was running the Eklavya project like we do now in these workshops all the lectures, video, audio, recorded lectures, slides everything is released in open source. Even these are available on the website. However, it is not well known that they are available. So, what I propose to do is I will let him choose which lectures he actually wants to deliver physically. And in addition to those recorded lectures we will also tell people that these other lectures are also available. You can perhaps listen to them. Let me play one of the experimental skills. Now let us begin our discussion of the experimental skills. Here we will cover the following points shown on the slide. First we will illustrate what is the meaning of the scientific method with an example. Then we will see variables and errors in experiments. Then what is meant by control, precision and accuracy. And finally we will mention in passing how to fit a straight line to measure data. Let us look at the scientific method. What does it involve? One can broadly identify four steps in this method. First is the observation of phenomena. Then based on the observation and our thinking we come up with a hypothesis about some happening in the world around us. The hypothesis is some sort of an imaginative explanation for things which we observe. However it is not verified to be correct. So hypothesis is a sort of statement of explanation for the phenomena which is not yet verified to be correct. So it is mostly based on intuition. Then comes the important step of verification of the hypothesis. So here broadly there are three steps experiment, observation and inference. If one wants one can club this entire thing, step of verification all the three steps of experiment, observation and inference in just one word that is experiment. And after the experiment and the inference drawn from it you make a generalization to all situations which may be similar to that considered in the experiment. Now let us look at the various elements of this method in little bit more detail. See observation. Observation is not a passive acquisition of sensory information but a critical purposeful process needing a high level of awareness. This high level of awareness is very very important for being a good observer. Because when you say that you should be observant, what does it mean? What is it that you are supposed to observe? So when you ask a student if the student is doing some chemical reaction and then you tell him you be observant and see how variables in the reaction are changing. The point is you are not telling him what are all the variables that the student should observe. It is not possible to tell also because after all you are doing a new experiment it is your duty to be aware as much as possible to identify as many variables which may be affecting the experiment. So it is in this sense a very high level of awareness is what is expected if you want to be a good observer. Because you cannot tell beforehand what are the things that you should observe. So for example you are doing a chemical reaction and you are concentrating on measuring the temperature. But at the same time the reaction is being done in an environment where there is light because otherwise you cannot see what is going on. It is possible that lighting may have an effect.  Depends on the awareness whether you are able to observe the presence of a variable which is affecting the reaction. So there is a reason why we choose to observe a specific portion of the whole domain of possible objects of observation. So it is not as though something that is very evident to your eye or something that can be heard very clearly alone is chosen for observation. You are aware of several things that are happening around you but then even though you are aware of all the things you choose only a part of those things that you are aware of for critical inquiry and careful observation. Hypothesis. Hypothesis is an imaginative preconception or an inspired guess about some particularly interesting aspect of the world. Every discovery begins as a hypothesis. Now hypothesis is based on intuition it may or may not be correct. We will illustrate this with examples. What is experiment? Experiment is an act undertaken to verify a hypothesis. It discriminates between possibilities and gives direction for further thought. This is another role of experiment. It discriminates between possibilities. It is a happening device to apprehend the truth. So it is a set of conditions that you ensure in order to observe a particular thing. So for example if you want to detect the wave nature of matter then you have to devise conditions, special conditions so that this wave nature will become evident. If you want to detect the particle nature of light you have to devise special conditions to detect that particular aspect. For knowing the wave nature of light you may not have to devise special conditions because already the conditions which are existing in the environment may be sufficient for you to observe easily the wave nature of light. So here you are not devising special conditions. It is a method of discovering causal interconnections. So what is experiment? Another way of looking at experiment is it is a method of discovering causal interconnections. Hypothesis. Devising a hypothesis that can be tested by practical experiments is an art. So every hypothesis may not be possible to test every hypothesis in a scientific way or to establish whether it is true or not. For example hypothesis all men are mortal. It is not something that you can test. It is not possible to scientifically examine this hypothesis. All men are mortal. Then how do you frame a hypothesis? That is also important. So there is a method of framing the hypothesis. It is called null hypothesis. That is hypothesis stated in negative terms. I will leave it as an assignment to you to see this point in detail. What is the meaning of a null hypothesis or framing a hypothesis in negative terms? In a very simple way I could put it as follows. Suppose you make a hypothesis, some conditions a result in effect b. So a implies b. That is your hypothesis suppose. Now an equivalent statement of the same hypothesis would be if there is no b there is no a. a implies b is equivalent to saying b bar implies a bar. b bar means not b. Supposing you are making a hypothesis some variable a results in an effect b. It is same as saying if you do not see the effect b then it means a is not present. Not b implies not a or no b implies no a. Now this statement and any of these statements are equivalent. But when you frame the statement in this form not b implies not a. No b implies no a. That is if you do not find the effect b then you can be sure that the condition a is absent. This form of framing the hypothesis is called a null hypothesis. Normally people say that to test a hypothesis it is better if you test its null form of a hypothesis. So more about this I leave it as an assignment because framing of hypothesis itself is a important and there are several details about this. Now we will consider an example to illustrate this particular aspect of the scientific method. West one observes a high level of prevalence of obesity. So there is a large number of people who are obese. In fact about 50% of the population is overweight. This is an observation. So naturally people are concerned about it. So some scientist working on the issue of obesity and removal of obesity. They hypothesized that the overweight people are overweight because they have a higher level of hunger than the average weight people. Because they have a higher level of hunger they eat more and therefore they become overweight. So the fact that people are overweight is one observation. The fact that overweight people are seen to eat more is also an observation and then you are trying to frame a hypothesis by intuition. What is the cause of overeating? What is the cause of overeating? So the cause of overeating is more hunger. Now some scientist came up and said look I do not accept this hypothesis that the hunger, the higher level of hunger is the cause of overeating. I want to test whether it is true. So he suggested an experiment or rather he carried out an experiment. Now his experiment was as follows. He took 100 overweight people and 100 average weight people. This group of 200 people was divided into two groups of 100 people each. Each group of 100 people had 50 overweight people and 50 average weight people. Now each of the two groups were given sandwiches to eat. So one group of 100 was put in one room and each person was given one sandwich to eat. The other group of 100 people was put in another room and they were given three sandwiches to eat. People in both the rooms were told that if they do not want they need not eat or if one sandwich is not sufficient to satisfy their hunger they can go and fetch another or more sandwiches from room which was kept about 50 meters away. So they can bring sandwiches from there and eat. If one sandwich is not sufficient. Now after carrying out this experiment they measured what is the average number of sandwiches eaten by the overweight people and the average weight people. Now very interestingly they found that on average the average weight people ate only one sandwich in both the rooms. So in the room where I am sorry I correct myself the average weight people ate two sandwiches in both the rooms which means in room number one where only one sandwich was provided most of them fetched one more sandwich. In the second room they left out one sandwich they did not eat all the three sandwiches. However overweight people the behavior was different. In room number one most of them ate only one sandwich whereas in room number two most of them ate all the three sandwiches. Now this experiment showed that internal factors such as hunger may not explain this observation because in this case I mean it depends on the experimental conditions sufficient care was taken to see that everyone was sufficiently hungry and so on. There are many other details of the experiment so which we will not go into here. We will assume that conditions were maintained identical in both rooms. But what it showed is that for the overweight people the amount they eat depends on the availability of food which is an external condition not an internal condition to the person. So the eating habits of overweight people are stimulated by external conditions in the environment more specifically availability of food. For the average weight people however there is an internal control mechanism independent of the amount of food available they will eat right some amount that is controlled. So this experiment therefore showed that you cannot assume hunger as the cause or higher level of hunger as a cause for over eating. Of course there have been further experiments and so on whatever I have said is a simplified form of the situation. But nevertheless it illustrates the importance of scientific approach. So what is the scientific approach? Scientific approach is you must verify the hypothesis nothing is accepted until you test and you must devise an experiment. So that is also important in science how do you think of an experiment to test your hypothesis and testing of the hypothesis does not mean that you should prove it even if you disprove a statement right even if you disprove a statement it is significant. Now the lack of scientific method however or scientific approach is very prevalent in society. Now before I give an example of a non-scientific method right I want to emphasize the fact that it is possible that not every hypothesis can be tested we have already said this okay. So there are many things which you may not be able to test by the scientific method devise an experiment and test and you cannot say that what is not possible to test by scientific approach is not true that is not the kind of thing the statement that we are making. But for our purpose of research right in a wider philosophical sense it may be true that everything cannot the truth all aspects of truth cannot be scientifically tested it may be true here we are only talking about research in science and engineering or humanities even humanities where you can test things scientifically. But when you say testing scientifically you should be clear what it means. So what it means is in a scientific method two important elements are there a hypothesis and an experiment. So both things are important an example of not using verification it happens very often in life but a significant example of this is the belief of I forget whether it was Aristotle or Socrates okay one of these two. So this philosopher believed that women had less teeth than men. Now this is a hypothesis it was based on intuition and once since the philosopher was well established and well known people also believe this statement and this happened for several hundred years. Now no one attempted to ask a woman to open the mouth and simply test check how many teeth she has this is very interesting why because the person who made the statement was very well established and regarded as a good thinker. So we must be aware that very often we might use non-scientific approach and we may have beliefs which are not tested we must always try to test the beliefs as far as possible okay. So this is an example of thinking based on only intuition very often all our hypothesis are based on intuition without intuition you cannot work. So we are not saying that you know intuition is bad intuition is very very important in fact only intuition can give you hypothesis but intuition is not sufficient in scientific working in working by scientific method intuition alone is not sufficient you must verify the verification or experiment is very very important. So now let us look at some other aspects of experiment conducting experiments types of variables independent variable stimulus or input or causes all these are synonymous terms. So this is the condition manipulated to determine its effect on an observed phenomenon then some variables can be dependent variables. So dependent variables or response or output or effect so this is the condition that appears disappears or varies as an independent variable is introduced removed or varied very important point in some cases it may be difficult to decide which of a pair of variables is the cause and which is the effect. So just because you see there is a relationship between two variables two variables are correlated does not mean you will know which one is the independent variable and which is the dependent variable then apart from independent and dependent variables you also have another type of variables they are called confounded variables confounded variable is one whose effect cannot be separated from the supposed independent variable. Now we will we can illustrate this with example suppose you are trying to find out if men and women have any specific preference for colors you want to now this is a hypothesis that you want to test whether there is a specific preference. Now you think you take a group of men and group of women and then you do some experiments with them okay and you find some difference and you try to attribute that difference in preferences to the gender but what you are not taking care of is the fact that this women men and women are they have a particular age. So over the years they might have been exposed to particular type of colors this is called past experience you do not know supposing because people are exposed to a particular type of color they like it they may develop a liking for it now this past experience is something it is a confounding confounded variable because it is effect you cannot separate out very easily. Therefore if you can devise an experiment in which you can separate out the effect of the confounding variables or confounded variables then that is something significant. So one must always be aware that there can be dependent variables there can be independent variables and there can be variables whose effect cannot be separated from that of other independent variables and confounded variables. So your experiment should not have confounded variables or you should have some method of eliminating the effects or at least if you cannot eliminate you can at least state in your experiment that this is a confounded variable whose effect we have not been able to detect. Some other attributes of variables quantitative variable it is something that varies in amount you can assign a number for it categorical variable it varies in kind gender is a categorical variable right male or female continuous and discrete variables. So you can have variations of quantities in discrete manner or continuous manner now we have discussed the various types of variable in experiment let us look at another very important issue any experiment you are making a measurement without a measurement there is no experiment I have emphasized this fact in my introduction that measurement is very very important just qualitative understanding of how when one variable is increased the other variable increases or decreases is not sufficient that is that does not complete the experiment you must measure. So that is where errors come in so two types of errors can be there in measurement random errors. So random error varies and equally likely to be positive or negative it is an error which is equally likely to be positive or negative as against this a systematic error is something which is constant within course throughout the experiment the word constant is to be not to be taken literally in fact if you want you can say non random errors so random error is one which varies equally likely which is equally likely to be positive or negative that is nature of random error but systematic error it has a certain trend predictable trend traditionally the word systematic error has been used therefore we will retain the error retain this word but you can understand this as a non random error and now let us illustrate with example supposing you are measuring the terminal velocity of a ball in viscous medium like glycerin suppose this is the experiment you are doing now let me draw a diagram to show that so this experiment all of us who are in engineering or physics would have done in our first year now this is a jar or a tube and it is filled with glycerin which is a viscous medium and you drop a ball in this medium now the ball initially accelerates downwards because of gravity but ultimately it acquires a constant velocity because as its velocity increases the viscosity produces a frictional force which increases with velocity so for some velocity the downward force because of gravity is exactly balanced by the frictional force or opposing force because of the viscosity of glycerin if you were to drop the ball in vacuum then it would accelerate continuously it will not reach a constant velocity experiment is to measure the terminal velocity of this ball terminal velocity is a constant velocity that it acquires after some time now how will you measure it the common method of measuring is you note for example when it crosses this particular mark with a stop clock so you start a clock then when the ball crosses a different mark you stop so the clock would have come somewhere here some time has elapsed now you measure this distance and measure the time and then the terminal velocity is given by distance by time so this experiment so in this experiment what are the sources of error and how do you classify the errors as random and systematic as shown in this slide random errors can occur in starting and stopping the clock or in estimating the ball location on a scale okay so let us look at the diagram again now you say you are noting the time when the ball crosses this mark now are you noting when the bottom end of the ball is crossing the mark or when the top end of the ball is crossing or is it that you are noting the middle this is one point and it may not be possible for you to precisely note any one of these so there can be some error because you are repeatedly when you do the experiment repeatedly right this something that you are not able to determine precisely and it can be random then starting and stopping of the clock you are looking at the ball and at the same time you have to start the clock so there can be a delay between the two events so you may start the clock before the ball has crossed the particular mark or you may do it little bit later and this thing cannot be controlled so these are the two sources of random error in this experiment these are examples of two sources of error which are random now what is the systematic error here that can happen supposing your clock after you start progressively become slow this is an example of a systematic error or when you repeat the experiment what happens is the there is a friction between the ball and the glycerin now this friction causes the glycerin to heat up after all how is the energy dissipated how is the friction the energy dissipated because of friction it is dissipated as heat so the temperature of glycerin will go on rising if you take a very long time to complete your experiment so this is another example of systematic error so like this in any experiment you have either systematic errors or random errors now you should have the ability to distinguish between random and systematic errors and you should also be aware of the fact that these errors are present and what are the sources of these errors because only then you can reduce the errors it is very very important to reduce the errors we will concern example to illustrate why reducing errors is very very important so before we go to that particular example let us see some further facts about errors we normally use the terms accuracy and precision so what is the meaning of accuracy now on the left hand side here you see a point or a circle which can be regarded as a true value of the particular variable being measured and the crosses around it indicate the values obtained in repeated experiments of the same to give you an analogy in fact you can regard I imagine that this is this represents a shooting event where the solid circle is a target and the crosses indicate the places where the bullet strikes okay when a person is trying to shoot at the target in repeated trials now you will say that the marksman is accurate if all these places where they bullet hits that somewhere near the target are very close to the target all of them should be very close so what it means is both systematic and random errors are small so random errors are represented by the differences between the repeated measurements and systematic error is represented by the difference between location of these crosses and the target so here for example when all these crosses are very close to each other but they are located away from the target then you say that the measurement is precise but inaccurate so precision has to do with ability to repeat the value in successive measurements several trials so you may be getting the same value in repeated measurements that doesn't mean it is accurate it means it is precise so accuracy means these values should be very close to the true value so systematic error should not be there precision means random errors are minimum okay but that doesn't mean systematic errors are absent so imprecise and inaccurate both systematic and random errors are present so this is an important point that we should note the difference between precision and accuracy so precision means small random errors accuracy means both systematic and random error should be small now when you write the reading let us see what are we pointing towards the systematic error or the random error now here for example on this slide you show the measurement of a resistance in some experiment and you write the measurement as the measured value as one particular number plus or minus another number so in this case does plus or minus 0.001 ohm represent a systematic or random error what does it represent evidently it is random error because it is plus or minus so it is equally likely to be positive or negative so it is not systematic error so note that in when you report your measurements in this form you are specifying the random error you are not specifying the systematic error now how do you detect and minimize errors this is the next issue random errors can be detected by repeating the experiment so when you repeat the experiment if you are getting different values then you become aware that there are random errors in the experiment however repeated measurements may or may not reveal systematic error this is very important you cannot reduce systematic error merely by repeating the experiment systematic errors are somewhat more difficult to detect and reduce random errors can always be eliminated by repeating the experiment so many times the research scholars are not aware that when they are minimizing error by repeating the experiment they are only removing the random error or let me not use the word remove they are reducing the random error you cannot remove systematic errors by this approach so first of all many times in fact the research scholars are not aware of the errors at all now how do you know whether a research college is aware of errors or not it you can easily see the way the readings are presented in graphical form measurement okay for example if you find that some measurements are reported like this so I show points these are measured points the measurement of y as a function of x and then you say the behavior is something like this now clearly the person who has drawn the diagram is not aware of errors because you assume that the measured value is precisely this point right whereas just now we have shown on the slide that supposing you are reporting measurement of resistance you will report it as a value that you have read on the meter plus or minus a quantity plus or minus a quantity that is a random error now I will not discuss in detail how do you decide the random error in a situation right you can look at it I am just initiating the whole discussion about the errors so how do you know the research scholar is aware of the errors well if it shows an error bar if it shows the reading as a range and then this value is the midpoint of this range then you know that yes the research scholars aware of the errors now why is this bar very important because now you see if I take lowest point here the highest point here because this is also possible and then the lowest point here then I do not seem to discern any specific trend okay but then you may say this will happen all the time the point is what is this what is the length of this bar this is what is important if the length of this particular bar is small then you can definitely discern some trend but if the length of this bar is long which is what we have seen in our lectures yesterday when we discussed about graphical approach and so on okay how to represent data in graphical form then you may not be able to discern trend any trend in such a case if you are reporting that you have discerned some trend then your conclusion can be in doubt now how to minimize random error you do it by averaging now how does averaging reduce random error let us look at this point also now before we do that let us look at the aspect of control in experiment when do you say an experiment is well controlled so control implies awareness of all the variables in an experiment and the ability to vary them at will so you should be aware of all the variables in the experiment and you should be able to vary all the variables the way you want this enables one to restrain sources of variability in research control also means a standard against which the effect of a particular variable can be compared so you are comparing against a standard the measurement against a standard the effects of all but the independent variable can be eliminated okay effects of all variables except for the independent variable now as we have mentioned in one of our earlier lectures the several independent variables can be there and then you will have one effect now how do you find out what is the relation between the different independent variables and the dependent variable so when you want to determine this you must have one independent variable being changed and monitor the effect and at that time the effects of other independent variables should not be there this is one important thing that you should ensure in your experiment this is what is the meaning of control another meaning of control now how do you can how can you ensure that so there are several ways of ensuring depends on the situation so the effects of all but the independent variable can be eliminated by either removing them if you cannot remove them by maintaining them constant or by screening them there is a method called screening you can screen the effect or by counterbalancing counterbalancing means you cancel the effect of one variable with the other variable and there is another approach that is called systematic randomization now all these various methods are very very important I do not have a time to go through them you can note down these words such as screening counterbalancing and systematic randomization and you can try to find out yourself this is an assignment because removing them one can understand maintaining a variable constant this is also clear screening what is the meaning of screening it is clear but how do you do screening right please find out how do you do counterbalancing some practical examples and how do you do systematic randomization we will see some example of how you can remove the effect when you cannot how you can remove the effect of the variable other than independent variable when you cannot remove the variable or you cannot maintain it constant one example we will see now how can there be difficulty in control let us take some examples to illustrate how difficulties arise in control of experiments concern experiment related to magnetostriction so what is magnetostriction the experiment for measuring magnetostriction is shown on this paper slide so magnetostriction means change in the length of the material because of magnetism change in the length of the material because of magnetism that is magnetostriction you know that when you heat some material it will elongate so that is change in length because of heat like that you can have change in length because of magnetism now supposing you are doing an experiment to detect whether a particular material has this property of magnetostriction so a schematic diagram of the experiment would be like this so you have a solenoid to create the magnetic field and inside this solenoid inside this coil sorry you have a coil to create a magnetic field and then inside that you put the material for which you want to measure the magnetostriction now when you switch on the current magnetic field is created and then you make the measurement of the length from this end to this end and you indeed find for example suppose the length has increased supposing in a particular situation you found the increase in length was say 0.005% increase in length because of magnetism now you are happy that you know yes you have detected magnetostriction in the material but unfortunately what you have failed to notice is that when you pass current through the coil the coil gets heated up and because the coil is heated up the material is heated up and because the material is heated up it will expand now are you sure that the expansion that has happened that you have detected or measured is solely because of the magnetism and not because of the temperature so what you have to do you have to measure the coefficient of expansion because of thermal reasons of the material separately and then you should try to see whether the expansion that has occurred here is more than that or you will have to find some method of measuring keeping the temperature constant but this is an example where you can see that when you want to increase the magnetic field the temperature increases okay so these are the kind of difficulties which are there in control another example terminal velocity of a body in viscous liquid like glycerin we have already discussed the apparatus by which you measure the terminal velocity now as we have said the temperature of the glycerin can go on increasing as you increase the number of trials of the experiment so now if you are measuring the terminal velocity as a function of for example diameter of the ball you are doing an experiment to measure terminal velocity as a function of diameter suppose this experiment then you have balls of different diameter and you are going on doing experiment with the different balls and you think that you have seen some trend as the diameter increases terminal velocity increases or decreases whatever you have seen some trend and you think that is because of the viscosity of the medium but the temperature of the medium has also changed so how do you know that the terminal velocity behavior that you have measured is not because of temperature right and because of viscosity alone so here again there is a problem in control then the third example is something that I already mentioned gender differences in color preferences gender is confounded with past experience so past experience confounding variable now in the previous examples the effect of temperature is the confounding variable okay in magnitude restriction experiment and terminal velocity experiment now why should one be bothered about precision why should one try to be as precise as possible so when experiments give results at variance with theoretical ideas new discoveries are made right this is the main reason why you must be bothered about precision let us consider two examples where precision played a role in great discoveries discovery of argon by Rayleigh and Ramsey this is first example now how was argon discovered the people knew that air contains nitrogen oxygen and traces of water vapor carbon dioxide and so on this is what people had known before argon was discovered now someone did an experiment to see the density of nitrogen that you get in two different to separate methods of getting nitrogen so one approach was you remove the oxygen from air and you try to remove the moisture and so on also since you are not aware of any presence of any other gas so you assume that when you remove oxygen and traces of moisture and so on what is left with nitrogen so you measure the density of the remaining gas let us put it like this now you think it is nitrogen that is your hypothesis another experiment was done where nitrogen was produced from ammonia that approach produces pure nitrogen you are very sure it produces nitrogen it was found that the density of the air that is left when you remove oxygen and moisture and so on was very marginally higher than the density of nitrogen that was produced from ammonia now marginally means how much it was just half percent higher now many times you may say this half percent kind of error can occur in your measurement anyway why bother about it but then when they did the experiment very precisely where this half percent also become significant then and they investigated the cause of this discrepancy they found that you can explain this discrepancy by assuming that there is one percent argon another gas of a particular weight and so on which they called it as argon so one percent of argon was you know detected and that is how the argon was discovered so you can see how precision is very important another example of discovery because of very high precision in experiment discovery of deuterium by Birge and Menzel 1931 and Ure Brickwede and Murphy 1932 how did this discovery occur so people produced hydrogen in two different ways and tried to measure the mass you call it as atomic mass one method was chemical determination as shown on this slide the chemical determination method it gave the ratio of the mass of hydrogen that was obtained by this method to mass of oxygen with atomic mass of 16 particular isotope now this measurement was reported as shown here that is 1.00799 plus or minus 0.00002 in a different experiment the mass of hydrogen ratio of similar ratio mass of hydrogen to mass of O16 was found to be 1.00778 plus or minus 0.00005 now 1.00799 plus or minus 0.00002 what this means is your numerator can be anywhere between 1.00797 to 1.007801 numerator here however the numerator can be 1.00773 to 1.00783 now you see that this range is definitely lower than this range even when you include the errors so differently here the mass of hydrogen was different in this particular experiment than in the chemical determination method now once this difference was detected and then it was hypothesized that you can explain this difference if you assume a very small percentage of hydrogen with atomic mass of 2 instead of 1 that is deuterium so if you assume one part of hydrogen atom with atomic mass of 2 you can explain this discrepancy and that is how with further experiments it was shown that yes this is indeed correct spectrum of hydrogen was taken in a very sensitive experiment and then it was found that you did have lines corresponding to a hydrogen atom of having a mass of 2 units so it is another example where precision is very important so if your this plus or minus value was much larger you would not have detected any significant difference in the two cases so this where it was very very important to reduce this these numbers which means you want your measurements to be made very precise so this is how precision is very very important in our experiments so we can reemphasize what we have said just now with another example significance of results depend is on precision if for example the measured resistance at two different temperatures is 2.0025 and 2.0034 we can say that temperature has an effect on the resistance can we say this yes if the error is plus or minus 0.001 ohm no if the error is plus or minus 0.01 ohm why because you can see that if the error is plus or minus 0.001 ohm then your values of resistance at 10 degree centigrade can be 2.00.024 2200.026 and at 20 degree centigrade it would be 200.033 to 200.035 now clearly the higher value here the lower value here is significantly more than the upper bound here so clearly at 20 degree centigrade the resistance is different than at 10 degree centigrade so you can say yes temperature has an effect but supposing your error was 0.01 ohm then your values would be 10 degree centigrade 200.015 to 200.035 this is one range that is possible at 10 degree centigrade at 20 degree centigrade it is 200.024 to 200.044 your measurement could have been anywhere in this range now you can see that 200.024 the lower end lies in between 200.015 and 200.035 so supposing these were the actual values then you find that as a function of temperature the resistance is decreasing on the other hand if these were the values it is increasing so you cannot discern any particular trend from here so this is how precision is very very important so if you plot the same thing on a graph I have now shown it in terms of numbers I will leave it as an assignment that the same illustration can be much clearer if you were to plot the things on a graph your graph would look something like this when the error is small your two readings at 10 degree centigrade and 20 degree centigrade this resistance this is temperature they would be like this so the maximum value here is less than the minimum value there so you can clearly see yes there is an increase this is when the error is 0.001 if the error is 0.01 what would happen is on a graph it would appear like this 10 degree centigrade 20 degree centigrade this is how it would be so now you cannot say you may it may also be that the resistance is not changing at all or it may be that it is decreasing or it may be increasing but in this case it is very clear so this is how this actually represent this length represents the precision or the extent of random errors how much precision now we have seen that precision is important now how much precision we should aim at it depends on the purpose of the experiment if a resistance is to be used as a standard in the range 10 to 20 degree centigrade and the precision required is 0.01% an error of 0.01 plus or minus ohm is adequate and it is unnecessary to reduce the error to plus or minus 0.001 okay so in your experiment you should have an idea of how much precision is required so this is another skill that you should have now each of these points can be discussed in great detail with further examples so you can have several hours of experimental skill right courses on experimental skill so here I am by just pointing out the important issues you can read up on your own you know what kind of research you are doing the goal of this discussion is to make you aware of the various issues you can you know read up the required material and then understand these issues in depth