Hi, everyone. I'm Stephanie Paterick, Adweek's executive editor, and we are starting a brand new live show today. This is our first time recording. It's called Adweek Together, and the whole purpose is to have a moment in the middle of the day to just touch base about how we are all navigating the new normal. So we're going to have, you know, sort of a rotating class of hosts and guests starting with our staff. Today you can see I'm joined by Chris Arons, my amazing colleague. He is the managing editor of Adweek's newsroom and also the director of our visual newsroom. So he has a background in video, which is coming in handy right now. It is for all of us on multiple levels. Thanks, Steph. Absolutely. And you're going to be hearing from different staff members each day, just about what they're seeing sort of in their different areas, you know, how the coronavirus crisis is playing out on all of the beats that we cover and all of the industries that we cover and serve. I'll say too that we really are hoping to connect with you. We'd love to bring our readers and our viewers on as guests as well. So while this week we'll be starting with Adweek's staff, next week we'll be looking to, you know, sign you up to come onto this show and talk with us about how you're navigating this, you know, your agency and your brand and your tech company. And we're going to be sharing everything from, you know, the business implications of this to also very practical how you're handling working from home, as so many of us are now. I'll say that you might see a cameo from my three-year-old or my mini schnauzer today. Anything could happen. So Chris, you know, to start as managing editor of our newsroom, you have played such a pivotal role just in the last week of moving 50 journalists, you know, from our offices on Madison Avenue in New York, you know, into each of their homes and making sure that we were still, you know, serving readers. I can say last week we published 230 stories on adweek.com. About 130 of those were about coronavirus alone. And then we also put out a print issue in the middle of all this too. It came out yesterday. So Chris, what has that a very quick shift been like? How have you navigated that? Yeah, it's truly been a team effort. That term has been tossed around a lot these past few weeks. Technology has helped. Everyone has gotten up to speed on how we use video conference for Slack. Slack and the office was always sort of just a chat function. Of course, Zoom has played an important part in all of us getting together for editorial meeting every morning at 10.30. And then throughout the day, you know, we are already a remote newsroom in a lot of ways. We have editors across the country, important in Birmingham and reporters in Austin and Minneapolis. And so we're sort of feeling what they feel on a daily basis, all working remotely. But as you said, we did put out an issue last week. And I know you can talk a little bit more specifically about that. But it was it was a genius cover by Lisa Granitstein, our editor of taking a Zoom capture from a Deutsch New York Zoom conference as they were navigating their new normal. And then talking to experts from our different advisory boards at ADD, just for their take where last week was week one, this is week two, and it's going to be many more weeks from here on out for our company and for so many brands and agencies and tech companies. Everybody like that. Yeah, absolutely. No, I think just the story of how that story came together is pretty amazing. We had obviously, you know, we work weeks in advance on our print cover stories in particular. And we had a different story planned for this Monday, pivoted quickly last week and put out essentially, you know, a quick survey to, you know, several dozen, you know, CMOs, from agencies, from brands, and got back responses from 16 of them really fantastic real time responses about how they are again navigating this in the moment. So we heard from Martin Surrell, we heard from David Kable Shindani, a president of the McCann North America, Colleen DeCorsi with Wyden and Kennedy, Rob Schwartz with TBWA, so many people weighed in. It was just really, really great to kind of get their candor in the moment. One example, I'm actually pulling it up on my screen here, Davika from McCann was talking about how to navigate a crisis and she said that Churchill said, never let a crisis go to waste. And we aren't, we're more deeply adopting technology like Microsoft Teams and other new approaches to building culture remotely, which will allow us to emerge from this stronger. So I think that's kind of interesting just her pointing out how times of crisis really be moments when innovation accelerates, right? We all have to move faster, think on our feet. We mentioned, we ourselves have probably 15% of our journalists are remote all the time. And yet we've never used video conferencing. We always just do like a dial-in. And I've heard from so many of our remote employees about actually how amazing the last week has been because now they really feel connected, they can see us all on Zoom. And Chris, maybe you can share a bit about the cover as well. I think that that image has become so iconic. Yeah, in addition to that, but I'm gonna, Nick is producing this, he's behind the scenes actually cutting the shots in and out. The other thing that Lisa, Granice and her editor did in the magazine was an editor's letter. What she did is she took one of our Zoom happy hours that we did last week as sort of the cover art for that visual. And it just really shows how that kind of technology is being used across the industry just to be able to communicate. So that's just one of the ways. One of the other things that we started at ADRI pretty early on and a lot of publications also did this was just tracking how this story had developed. In late January or February, it was a health story. It was something that a B2B publication wouldn't necessarily cover. Well, that quickly turned by early February into something, yes, we're going to be covering this. So not how do we cover it. So by early March, we had a tracker that monitored all of the cancellations of big events, South by Southwest being of course the biggest one. And then it turned into the shutdowns and the stay in place orders, which affected just every business you can imagine, restaurants, businesses. And so the trackers been trying to update our audience on all of those sorts of things too, that retail stores closing restaurants closing, you know, whether they're mom and pop restaurants or the big chains McDonald's and etc. So that's all that's one way we've been able to sort of update our audience on a minute by minute basis of how it affects them, both as brands and agencies and consumers. And it is, I think you're hitting on something that I'm hearing from so many people is just how quickly the situation changes and the news cycle and our understanding of it changes. And I'm thinking back to, you know, the Monday after South by Southwest announced that it was going to cancel. And the team leaders in our newsroom all got together and we had, you know, like a long brainstorming session about just, wow, what is the fallout of South by Southwest cancelling and all of the activations that were supposed to happen, all the announcements that were supposed to happen, how our business is pivoting.  And now to me, South by almost feels like a flip out here in New York, where we have this week, all non essential businesses, closing or moving remote. And so yeah, our trackers just one example of how we've had to keep, you know, evolving our coverage, what started as a cancellation tracker is now a broader economic tracker. Right, absolutely. And Robert Clair, who covers brands for us and has for many years had a great story last week about how some of these brands, they're not selling products, they're giving them away. Can you talk a little bit about that and what Robert brought to the fore in that story? So this was the second most popular story on our site last week. The most popular one was actually about how corn hubs traffic has changed as we've moved to a remote, you know, a work, a work from home culture. And as the work day has been disrupted. Josh Sturmburg wrote that one. Our second most popular story was about how brands, yeah, are really sort of using this as an opportunity to build goodwill with their customers.  And I started handing them out, I think like on the side of the road. So it has been neat to see brands sort of taking it as an opportunity to superserve their customers. On the media side, you know, we've seen a lot of media businesses lifting paywalls or loosening paywalls so people can read coronavirus coverage. We ourselves are making all of our coronavirus stories, even ones that would have been premium free, you know, as long as you're registered on our site, you just sign up with the email address, you don't have to pay and you can read anything we've done about coronavirus. Because something on my mind too is just the medical front. I mean, obviously, it's come to light. Just how much our hospitals and our doctors are going to be needing help in the weeks and months ahead. For personal experience, I can tell you I'm like seven and a half months pregnant. And we just got word, you know, last night that one of the largest hospital groups in New York will not be allowing partners at birth. So that's really big news. And so, Chris, I know you've been kind of tracking this about how companies are stepping in to help with supplies. What are some interesting things that you've seen there? Yeah, so Ford actually put out both as chairman, Bill Ford and its CEO and president on the different morning shows this morning, talking about how, you know, they had to shut down their assembly lines as, you know, mandated or guided by federal government and their state governments. So what they are doing is they're turning over their assembly lines and creating, turning them into to making ventilators, which, you know, it's hard enough to make a car all the parts that go into that. But as the president Ford described this morning, it can be just as complicated to make a ventilator. But they're going to do it. They're partnering with GE. They're also partnering with 3M. So major brands wouldn't ordinarily necessarily be working together just to get more of these ventilators into the supply chain. And they figure by the beginning of June, they could be producing 100,000 of these up into the hospitals for as long as this is going to be going on and necessary. So, you know, this is where this is where we are now. This is where the big brands are stopping with, you know, manufacturing, stopping what they normally produce to sort of get us through this and get the hospitals and the medical facilities, the protective equipment and the medical equipment that they need. Yeah. I think I saw something just this morning about H&M. I believe it was offering to start sewing, you know, like protective gear and masks and things like that. So I'm hoping we'll see a lot more of that in the days to come. Christian Seriano is trying to create the masks. So none of the fashion designer, you know, designing red carpet outfits. He's trying to get his folks as safely as they can to be producing, you know, the medical masks. Right, right. And it's like the Met Gala is one of the many things canceled. So what else are you going to do? Also, you know, I'd love to talk about the creative side of this because, you know, I do think we are going to see, we're just starting to see, I think, agencies and creatives step in here and do some public service campaigns. What have you seen on that front? Yeah, Auto, which is a huge television advertiser just because I've been watching a lot of TV as a lot of us have over the last few days, not just streaming but broadcast television. Well, but big car companies are still advertising and they've customized their ads given the current situation. Toyota hasn't had out there sort of problems together, kind of feeling. I saw Hyundai Spot this morning, which actually mentioned COVID-19 in their spot saying, if you've been affected by COVID-19, we're here for you. And no one's going to be, I can't imagine a Hyundai dealership, at least where we are in the TriStar area that's open now. But at some point, there's going to be some good will out there from somebody who's in the market to buy a car. And they're going to perhaps remember this and then also take advantage of these incentives that might be available because we just, again, don't know, talking about the economic side of this, what the job losses are going to be, what the total economic losses are going to be. And we leave that to the CNBCs and the Fox businesses of the world. We'll cover the brands and the advertising side of it. But one of the other stories that we wrote yesterday, Katie Gunstrom, who's our reporter down in Austin wrote this pretty cute story about how some brands are having to affect just their logos in this time, and the Chiquita Banana logo, where Ms. Chiquita has gone home. So it's just the yellow that we know from Chiquita Banana without Ms. Chiquita. Coca-Cola, their iconic logo, script logo, which goes back to basically the founding of the formula in the late 1800s, separating the letters just to show separation, the separation of that value from each other is what's needed right now. Yeah. And we had a story in our creativity vertical yesterday about a spec ad. So it wasn't even an official ad, but that somebody did for Guinness where it's sort of a black background. It looks like a Guinness pint with a couch, the color of foam at the top. And from a distance, it really just looks like, you know, a glass of beer and you look closer and you realize it's a call to stay home. Which our creativity editor, David Griner, was like, if you're going to do a spec ad, you got to knock it out of the park. And these people really did. Yeah, 100%. Yeah. You know, some big news this morning just speaking about advertising is the Olympics decided to cancel. They had to be dragging their feet. I think as early as March 17th, you know, they were saying that they were still supportive of going forward with it. But the Olympic Committee and Japan's Prime Minister, you know, announced that they're going to postpone it for one year. And interestingly, in the summer of 2021, they will still call it the 2020 Olympics. That obviously is going to mean a lot of things for NBC Universal. They had, they had booked, I think, 1.25 billion in ad sales around it already. 90% of the inventory was full. And, and also I think they were, they were really planning their campaign around releasing the Peacock streaming service. Thank you for talking about this. Am I right? That's right. Absolutely. Yeah. And, and we'll do a little plug here to promote tomorrow's show. I know you're going to be bringing on Kelsey Sutton, who's our streaming editor, who can talk more about that. But just what streaming has meant to all of us as we, you know, start this sort of new normal being at home. Absolutely. And on, on that note, I want to ask you before we, before we close out today, you've been working from home a week now. Actually, no, you were, you were a trooper. You went into the office a couple of days last week. Last Tuesday, I went in and I was like, no, this can all be done from home. Yeah. Chris is going down with the ship. Anyway, I'm glad that you're home now. I'm glad that you're being safe. And I'm wondering what tip would you pass along after working from home for a few days? You know, I was thinking about this earlier today. And, you know, I've learned how to be a better listener, frankly, sounds a little schmaltzy. But, you know, when you're in the office and you have someone coming up to your desk, it's that eye to eye contact when you're going to someone's desk and you're talking to them. It's much easier to listen in that kind of situation. We're going to have to for the next couple of months, you know, sort of rediscover how we listen to each other. If it's on Slack, if someone slacks you and has a problem because they can't get into the Zoom room, how do you react to that? How do you listen to them? How do you coach them through it? So I'm sort of like, you know, keeping that manager hat on and get the entire team through it and just trying to reach out as much as we can. I don't know if you're doing the same thing. And just to be a better listener in new and different ways. Yeah, I love that so much. I do think I am finding that I'm having to be much more intentional about my interactions because when we're all in the office together, you can kind of walk through the newsroom and get a vibe and get a sense of how everyone is doing. And it's very easy to have quick conversations, you know, in the hallway or at people's desks. And being home, I'm realizing, you know, there's no way to know how everyone is doing and what everyone is working on unless we really are intentional about it. So for me, I think, you know, something that that I've been trying to do is have a schedule where again, just to be intentional where my mornings are about meetings, both group meetings and also one on ones. And I've been trying to check in with people, not even necessarily my direct reports, but just having one on one video chats with people. And that's been really helpful.  And then in between, I take a walk. So anyway, well, great. I really, Chris, thank you so much for helping me kick this off today. And just for everything that you've been doing for our staff and for our readers. Thank you to everyone tuning in. It's really, it's great to have you here. We're going to be doing this at one o'clock, just about every day. So as Chris mentioned, tomorrow, Kelsey Sutton, who's our streaming editor and part of our TV team is going to join me to talk about, we'll talk about the Olympics, but also even bigger, if we're going to talk about, you know, what the streaming services are doing. This is actually a pretty key time for them as we are all home watching TV. And also just so you know, you can, you can find this a few places. So tomorrow at one, you can tune in on adweek.com. You'll see a story on our homepage that you can click through and just watch, watch this live right from our site. You can also watch it live on adweek's account on LinkedIn. And you can comment there too. So we'd love to hear from you. And then after it's recorded, it'll be posted on IGTV. So you'll be able, if you don't catch it live, don't worry, you can, you can still find it in three different places. One last thing I'll share is that we have an email account. It's adweektogether at adweek.com. And please write in and tell us if you're interested in being a guest. Let us know what topics would be useful for you, what questions you have. And we'll bring some of your questions and commentary into this show, you know, in the days ahead. So thanks so much again, Chris. Thank you, Nick behind the scenes. Thanks for producing and to all of our readers. Have a great afternoon.


Welcome to session 20 on our course on Quality Control and Improvement with Minitab I am Professor Insajit Mukherjee from Shailesh J.Maker School of Management IIT Bombay. So, ah last session what we are doing is that we are talking about two sample t-test and ah and how to use that in what scenarios and ah today we will extend that ah concept of two sample t-test and in what scenario the test are conducted that we will try to see. So, ah this was the two sample t-test example that we have dealt with that there are two catalyst over here and we want to improve the yields over here and we want to see that which catalyst is effective which is not effective like that. We saw that both catalysts are effective. So, in that case there is ah both catalysts are not effective. So, in this case what happens because of the p-values that we are getting over here this is more than 0.05. So, in that case both the catalysts are ah equally equally giving the same means or we can say that mu 1 population mu 1 and mu 2 ah for catalyst and catalyst b if we can say that one that way. So, I cannot reject the null hypothesis basically over here ok. So, there is no way improvement has happened with a different catalyst ah with an existing catalyst we can think of ok. So, this is basically a one factor at two level experimentation. So, what is one factor two level experimentation? This is a factor will be equals to catalyst and there are two levels level A and level B like that. So, this will be the levels we can we can say L A level and L B level like that. So, when we have one factor and we have over here catalyst A and catalyst B. So, this experimentation was conducted like that and we wanted to see the effectiveness of catalyst over here. So, two sample t-test is a starting point of experimentation what we do ok. So, in case the distribution assumption fails over here like catalyst A and catalyst B what we have to do that we can just check ok. So, I will show you the non-parametric options to this. So, two sample t-test we have we have proved that everything is working over here, but assuming that distribution assumption fails over here and in that case what is to be done we want to see. So, two sample t-test file we will open. In that case this is the catalyst A and catalyst B we can write over here catalyst A and this is catalyst B and we want to see the difference between these two. So, you have a non-parametric option over here to check this one and this case man witness test is the option that we have where median will be compared. So, one will be catalyst A and second will be catalyst B 95 percent confidence level and not equals to condition we want to check. So, I will click ok over here and what we will get is that these W statistics and P values will indicate whether the significant difference exist between level 1 and level 2 basically catalyst A and catalyst B like that using median values over here. So, in this case what we are seeing is that we do not see any difference between that. So, non-parametric test also confirms that there is no difference between catalyst A and B and then we can move ahead with this. So, this is non-parametric options. Now, one important thing that we also need to consider when we are doing experimentation and doing two sample t-tests like that we told that independency of the samples that is required like that, but scenarios can exist that some of the sample observations that we have taken over here may be one single sample and we have two observations over here. So, this is the subject that was so that we are recording cholesterol level over here. So, cholesterol level which was measured over here. So, 50 participants evaluate the effect of that and exercise like that. So, before and after exercise like that recordings data was recorded like that. So, we want to see that whether exercise has a positive impact on this lowering the cholesterol levels or something like that. So, total cholesterol was measured in each subject and then three months after participation. So, this was again recorded like that. So, we want to see over here. So, in this case this data over here before and after experimentation this before and after the that control and all these things exercise is expected to be correlated like that. So, whenever data is generally it is from the same subject. So, in that case what is expected that this is a PR data basically this is a PR data from a single sample like that. So, what is expected is that data will be correlated like that data will be correlated and for that two sample t-test is not the appropriate test that can be done. So, here PR t-test is generally recommended where the data is highly correlated like that or significantly correlated like that. So, how do we see that one? So, we will go to the data set like that. So, maybe we can this is the data set that we are having before and after over here C2 and C3 column that you see over here these are the two data set what we wanted to see and let us see the correlation between these data. Earlier we have seen independence here also we will see basic stat and correlation between the data set and we expect that there will be high amount of correlation that exists between the data and in options what you do is that we are keeping this in results we are PR wise correlation table we want because p value is required. So, when you do this the R value is around 0.7 and what you see is that p value that is reported over here. So, if I can enlarge this one I am copying copy as image over here and then I put this then and then I just place it in excel sheets. So, this will be placed in excel let us say and we want to see we want to see over here whether the whether fair amount of correlation exist or not. So, I will just enhance this one and I am just copy pasting this image over here and for that I will just enhance so that you can see like that and the p value corresponding is you can see that this is 0.003. So, it says that sample 1 and sample 2 which is before and after and before like that. So, they are highly correlated over here. So, in this case what they suggest is that statisticians suggest that we cannot we cannot go for two sample t-test over here most appropriate test over here is known as spare t-test there is a most appropriate test to check whether there is any difference between these two labels that is before and after like that. So, what they have suggested is that we have to calculate the difference and based on the difference and standard deviation of the difference what we can do is that there is a statistics which is used over here and what you see the formulation of this. So, this is the formulation what you see over here. So, this is the formulation that is used and D is the difference between this before and after over here. So, the difference average will be taken and then standard deviation of the difference and square root of number of observations that I have that is 15 observation or paired observation that I am having over here. So, based on this I will I will calculate the t statistics calculated value and corresponding p value will be calculated like that ok. So, we have ensured that there is high amount of correlation and in that case what is to be done is that I will go for paired t-test over here. So, this difference can also be calculated. So, if you go to calculator and use calculator over here what you can do is that we can we can just say before minus after over here and I want to save in C4 like that column number are given. So, this is the where I will save and I click ok I will I will find out the difference that is there over here and the assumptions that to somebody test this paired t-test assumption is that this data should be normal this data should be following difference should follow normal. So, that can also be verified over here basic standard normality test like that. So, C4 can be identified and we click ok and we will get a p values for this and what we can see is that p value is 0.404 and that satisfies our condition that means difference also follow normal distribution. So, I can go for a paired t-test. So, immediately what I will do is that I will go to basic stat and I will go for this option paired t-test over here and in this case what I will do is that sample one this this option will will be blank when you when you click this one each sample is in a column. So, this is the or you can give difference over here summary is data in difference is given. So, here what I will do is that I have already before and after observation. So, then what I will do is that in options I will not change anything I want whether the difference is equals to 0 not equals to condition both sided t-test I am doing over here. I click ok and in graph also if you want to see the box of difference like that box plot of difference like that you click ok and you click ok like that and you will get all the results. So, before the standard deviation mean is given over here and then confidence interval is given for the estimation of the mean spare difference estimation over here and that is a confidence interval that is given over here and then we have a key statistics which is given over here which is the test result which I can copy from here and I can paste it for viewing like that. So, I will paste it and I can just enhance this image over here. So, t-test says that p value is around 0. So, approximately and that is less than up to 3 decimal plus it is 0. So, in this case what we can assume is that there is significant difference between this 2 data that before and after data set that we are having. So, in this case the difference is significant over here. So, difference reduction over here is significant that we can observe like that. So, mean is also given over here. So, before 261 after 234. So, basically it has reduced cost if we are doing exercise and other dieting we are following. So, in this case this is and this is accurate. So, because we have taken pair t-test over here we can also do two sample t-test, but accuracy level somewhat decreases in case correlation is high we will lose some information we will lose some. So, over here what is suggested is that we will go for pair t-test rather than two sample t-test rather than two sample t-test which is recommended statistically which has been shown that pair t-test is more effective, but if there is no correlation much correlation over here I will not go for pair t-test I will go for two sample t-test like that. So, there is another example over here what we can see is that this is a moisture meter reading with some instrument over here and with an old instrument I want to see whether there is difference or no difference between old one because I want to implement a method new instruments which is more which takes a recording very quickly like that old methods may be taking long times like that 5-6 hours over here in minutes we are getting the reading, but whether the readings are accurate or not. So, old wave was accurate that was the condition over here and this is a new reading for a given sample. So, old reading and new reading as provided over here I want to see whether there there is significant difference between these two readings or not. So, in this case what I will do is that first I will go for basic statistics correlation coefficient whether it exists between these two variables. So, correlation I will go and I would like to check a new instrument and old instrument correlation coefficient and what I see is that r value is 0.889 approximately. So, if we announce this image over here what you will find is there is high amount of correlation that exists over 0.889 that is showing in this relationship diagram and if you go to the p value of this what you will get this p value is around 0. So, this value is around 0. So, I can copy this one and paste it over here for your convenience to see. So, this you see that p values are of approximately equals to 0. So, in this case what we can suggest is that there is higher amount of correlation. So, in this case what we can suggest is that go for PRT test instead of two sample T test. So, what I will do is that I will go to basic statistics and then I will go to PRT test and in PRT test what we will give is that new instrument and old instruments like that and I will give options over here that same I want to see the differences. We can do one sided also, but we are doing two sided. So, immediately. So, over here what you see is that new instrument and old instruments in this case one is giving 38.43 reading that is new instrument on an average. So, in this old instrument is giving around 35. So, there is a difference of around 3 minutes over here and that is significant that is shown in the PRT test that you see over here. So, this I can copy and I can paste it over here below we can paste this one and we can just enhance this and try to see. So, in this case also p value is less than 0.05. So, in this case what what conclusion we draw this we can draw is that the readings are different, the readings are different over here. So, in this case we can we can just say that the two readings are different. So, before and after readings are quite different. So, we will use PRT test whenever whenever there is a higher amount of correlation between between the samples means with the same samples I am taking two readings over here like in manufacturing we will find that I have hardness testing machines of different types with different tips like that. So, whether the when I use different tips whether readings are different or not. So, that to confirm that one also we do PRT test because sample remains same. So, in that case on the same sample I am using two methods like that I want to compare which method is giving me higher reading or their same readings like that or any of them will give the same hardness like that. So, for that also this type of analysis is required. So, this is the all about PRT test. So, then an options for this is nonparametric way if you want to analyze when it is not satisfactory normal distribution assumptions of the deviation is not satisfactory what can be done one sample will coxon test can be used. So, in this case let us say old and new one and we are taking the difference over here let us say D is the difference over here we can just calculate the difference. So, calculator can be used. So, in this case what we can do new instrument minus old one over here and I click and save it in let us say C7 I am saving it in C7 and I click ok over here the difference is recorded over here. So, difference is recorded over here and maybe it is not following normal distribution, but here it will follow normal distribution this is a classical example taken from book. So, in this case in case it fails what you have to do is that you have to go to nonparametric test and with this difference what you can do is that one sample will coxon test. So, in this case what you can do is that difference that we want to see and median value should be equals to 0 that is our assumption difference should be close to 0. So, in this case not equals to case we have taken. So, P value of this you can get. So, if I copy this image over here and I paste it like that. So, this observation and I paste it what I will find is what I will get is that the difference is equals to 0 not equals to 0 that is the condition I am testing and the P value approximately 0.001 which is less that means there is a difference significant difference within the that difference is quite significant that is why P value is less than 0.05. So, that is the alternative we have in case you are unable to satisfy the assumption. So, in this case we will prove for this nonparametric test one sample will coxon test like that. So, that is the overall idea when I am experimenting with one factor at two levels like that. Now, we will extend this concept to an important concept which is known as analysis of variance like that. So, for that what is required is that some understanding over here is required the same diagram I am using and these are the control factors which is in my control while doing experimentation I can change the levels of these factors over here x1, x2, xp. So, there can be P number of factors which can be controlled by the experimenters like that these are known as controllable factors like that. There will be input conditions or sample observations samples we need to go into the process like that then these parameters will be controlled there will be some noise variables over here or uncontrollable inputs like that or variables like that. So, in presence of this I need to determine the setting of this condition so that I get the best CTQs or output over here which is close to target with minimum variabilities like that. So, in this case, so for this two sample details what we have done is that we have assumed that x1 is a factor let us say in the process only two factors and there is only level 1, level 2 like that. So, if x1 has more than one level over here so level 1, level 2 and level 3 one possibility is that I do individual assessment over here whether level 1 and level 2 are different or level 2 is different from level level 3 mean is different similarly level 1 with level 3 like that I can do pairwise comparison like that. So, I can do two sample T testing and see which level is different from which one like that. So, why I am doing this because I want to see whether this factor x1 is influencing the CTQ or CTQ this is like screening I want to screen the factors and do some preliminary analysis so that I understand that this factor can be considered is full-fledged experimentation at a later stage. So, I want to see whether one of the factor is influencing the variable CTQs like that ok. So, I can experiment more than two levels like that. So, it can be two levels, but we can also experiment more than two levels for a given factor like that. So, in this case what is the best option? So, if I do pairwise comparison what will happen is that and I have to conclude based on this all pairwise comparison the type generally increases over here. So, what do you see is that whenever I am do so the null hypothesis over here is that all the means are same and alternative is any of the means is different from any of the means over here. So, there is different means when I not equals to j when I am considering this condition like that. So, there can be three different levels and three different means will be generated and whether they are same or whether there is a difference between the means of any two levels like that. So, when I am concerned about that we go for a one-way analysis of variance. So, what I can do is that I can compare mu 1 with mu 2, mu 2 with mu 3 and mu 1 with mu 3 like that and pairwise like that pairwise comparison is possible. So, what is shown over here this with this and then this with this like that and then this with this this is also shown over here. So, if there are three levels 3 C 2 basically we can do combination like that. So, what will happen is that if I am doing this combination over here overall judgment will be correct. So, that reduces like that. So, the type one error basically increases over here and in a statistical book you can see why type one error increases. So, in this case what is required is that to keep the type one error as 0.05 what we have assumed for an experimentation hypothesis over here. So, my level of significance will be always 0.05. So, for that Fisher developed this analysis of variance and where the level of significance remains 0.5 and I can make a conclusion based on this that I will be true 95 percent of the time. So, in this case this is a extension of you can think of two sample t-test like that, but there are more than two levels that we want to see over here. So, there are more than two levels and I want to check and, but there is only single one factor over here. So, there will be only one factor and that will have different levels and I want to check that whether when I change the levels whether it is basically impacting the CTQs or not. So, it is impacting the CTQs or not or mean CTQs or not that is our objective over here. I want to screen this factor and figure out that within the range if there is two or three levels of X 1. So, whether the mean of CTQ is changing or not. So, that is our overall objective and if it is so, then in that case X 1 is a critical variables which influences why and we can take it forward to full-fledged experimentation when we go for response surface methodology or like that. So, after full factorial when we are going for full factorial. So, in that case this may be one of means factors to be screened. So, here experimenters can do a simple experimentation with a single factor and see whether that is influencing or not and although it is always suggested that we take all together and do the experimentation, but initial studies we can do and try to screen that one and then go for full factorial. So, this is used for basic screening experimentation like that, but you have to remember that we cannot go for pair 2 sample t-test over here. So, t-test is not sufficient. We have to go for a F-test analysis over here which is given by analysis of variance like that. So, we have to consider that scenarios like that. So, let us take one example and try to understand the scenarios before we go into analysis of this this is known as one way analysis of variance basically. So, what we are doing over here is that we are analyzing variation basically, but difference between means we are trying to trying to report over here whether there is difference, but the variance information is used for that that is why it is analysis of variance basically. So, what it does is that so, one experimentation this is one example taken from again from Montgomery's book and what you see is that inside strength I want to maximize. So, in this case I am changing the hardwood concentration which is the only x factor that I am having and this is the only y I am monitoring over here. So, this is the condition and the hardness concentration the experimenters have decided that it should be between 5 and 20 that is the optimal range of x that we can take over here and it can have more than two levels like that. So, the experimenter choose 5, 10, 15 and 20 and this is the x level that you are seeing and these are the y observations that you see y i j we can think of observations over here. So, in this case I through and j th column we can think of. So, this is and there are total a number of levels. So, if you if you write the generalized form over here what you can see is that y 1 1 is the first observation like this there are n number of observations n equals to 6 over here. So, n number of observations so, this one will be y 1 n like that. So, first and there will be a levels like that it can have a levels like that. So, this is the data of general forms we can write. So, mathematically we can express this one in this way and then what we are seeing over here is that when I change the level from 5 to 10 or 10 to 15 or 15 to 20 is there any significant difference that is happening in the CTQs y CTQs over here. So, mean value whether it is changing in any two levels when I am changing over here. So, that means if any two levels it is changing significantly that means this factor is important and can be considered for the further experimentation like that. But assuming that there is no other factor and I want to maximize or optimize the levels so that where the hardwood concentration should be kept so that I have maximum tensile strength which is my objective over here. Let us assume that other factors are not prominent over here only one factor is there I want to select the factor over here. So, this is the first step of experimentation where we want to determine the condition where we will we will get maximum CTQs or CTQs can be maximized because my target is tensile strength. So, over here tensile strength higher the better. So, if it is higher the better that is the condition we want to achieve over here ok. So, one is 5 percent over. So, levels over here are more than 2. So, there are how many levels over here 4 levels that that you can see over here. So, A is equals to 4 that is the thing that we are assuming n equals to 6 like subgroup size what we have seen. So, this is n equals to 6 observation and there are 6 was a 24 total number of observations. So, over here in this matrix what you see 24 observations and all are random random of this this is experiment is done by randomization randomization. So, what is randomization? So, at 5 percent some one sample will be taken arbitrarily and 5 percent Hardwood concentration will be checked and accordingly what we will say that there is 6 specimen over here. So, in this case first specimen will be taken and what we will do is that we will run at 5 percent and observe the tensile strength. So, this is the 10 7 was observed tensile strength like that. Then I will randomize this means this data set is general this decision set is generated based on randomization that means sample will be selected any of the samples can be selected and any of the levels will be selected over here. So, this is known as complete randomization like that. So, we do not fix 5 and then do the experimental laws and determine all the 6 any all 6 observations should not be completed in one go over here. So, at 5 percent all 6 samples will be put and we will take that it is not like that what we have to do is that we will randomize this run over here. So, what will happen is that this is because of some reason which we will understand afterwards. So, what I am saying is that this is done randomization is done over here. So, levels will be selected randomly over here samples will be selected randomly samples are assumed to be homogeneous over here. So, in this case so sample to sample variation is very less only percentage variation what we are considering over here. So, at different levels we take 6 readings like that. So, we will have a average of this. So, y 1 average like that we can save over here. So, then y 2 average y 2 n average y 2 average over here second level like this first level like this. So, this will be y a average like that and then we can make a grand average over here. So, this can be a grand average like that. So, this is symbolic notation that you will find in Montgomery's books that is the symbols that I have written over here you can use a different symbol also. So, that is my overall objective over here is to determine the level whether it is 5, 10, 15 or 20 where the where the tensile strength will be maximized over here for that I have changed intentionally. So, this is systematic induced variability that I have I have considered over here I have changed the levels arbitrarily over here and then I have recorded the tensile strength and based on this mean value over here this and this and this I want to freeze a level where my tensile strength will be maximized like that. So, how do we do that that is important for us and we will we will discuss about that. So, that is the and what Fisher has given is that what Fisher has done is that Fisher has given a table over here which is known as ANOVA table like that and Minitab will report this ANOVA table over here where you will see source of variation sum of square over here degree of freedom and mean square calculation and F statistics that will be reported like that. This is important F statistics over here and it will be compared with a tabulated value and if this F is greater than this one. So, in this case he will come out to be less than 0.05. So, this is the process this is the process we make the interpretation like that. So, over here treatment means when I change from level 5 like that 5 to 10 or something 10 percent over here. So, treatment whenever I am changing the levels the total amount of variability that is that it that it creates like that. So, that can be calculated as and known as SS treatment like that. So, because of change in treatments which is level 1 to level A what is the overall variation that is happening because of these changes like that. So, that we can think of think of a sum of square measure. So, formulation is given sum of square measure any books will give you sum of square measures for treatment treatment means when I change the levels like that and the overall variations will be given like that and this is the overall variation that you see like that. So, this from the overall average out is differing like that. So, that can be considered as a individual average square of that we can take square of that variation. So, 7 from the overall average if you take the reference and square of that that will give you a summation all this will give you the sum of square total basically and variation due to treatment. So, there is formulation over here which you can see in any books like that. So, SS treatment will be calculated SS total is the total variability of the data. So, because treatment will not explain all variabilities. So, that that is the condition that is the SST will be SS treatment over here and and there will be some error SS error over here. So, Fisher has given you to a way to calculate this one and how to calculate SST formula is given from the given data set that is generated over here. So, from this matrix we can generate these values of SST we can generate SS treatment and SS error can be calculated like that SS error will be SS total minus SS treatment that is the formulation we can consider and degrees of freedom will be reported also over here. So, degrees of freedom means A number of treatments is considered over here. So, A minus 1 is the degree of freedom and total observation is 24, 24 minus 1 this is A n minus 1 is the total degree of freedom and if you subtract this A n minus 1 and then minus this treatment combination what you get is that error degree of freedom basically. When we have calculated this degree of freedom over here. So, SS treatment divided by degree of freedom gives you mean mean mean square treatment like that. So, this has to be calculated similarly SS error by A into n minus 1 this will give me MS error like that. So, then these two will be compared like that and the ratio will be taken MS treatment by MS error over here. This will give you a F 0 values like that this will give you a F 0 values over here and this F 0 value what you have to do is that this F 0 value has to be compared with tabulated value like that ok. So, this will have a degree of freedom A minus 1 over here numerator degree of freedom and the denominator degree of freedom will be A n minus 1 like this. So, F will be calculated at let us say alpha level of significance and this will be calculated and F 0 will be compared with this tabulated value over here and if this is greater than this in that case P will come out to be less than 0.05. So, we are going by P methods like that we are not going by tabulation and all this. So, P will indicate whether to accept or reject the null hypothesis which is null hypothesis over here null hypothesis whether the mean at different levels 5 percent over here and equals to 10 percent over here equals to 15 percent over here or this is 20 percent over here and the alternate hypothesis over here is any of this mu i not equals to mu j over here or i not equals to j like that that is the condition I am checking over here ok. So, here you can see the formulation that I have even I have written like that. So, this is will be compared and if it is better we will reject the null hypothesis basically. So, this is the overall theoretical aspect that is covered over here that means how to collect the data randomization is considered over here and n will be the subgroups what we are considering. So, this is also known as replicates over here, this is also known as replicates. In experimentation this is an important thing that we have to consider more and more I replicates what will happen is that more and more I will be sure of the final conclusion that I am drawing. So, but number of samples size will increase over here. So, total number of samples here 24 experimentation was carried out if I have taken only two replicates in that case only I have to do 4 into 2 8 experimentation like that. So, you have to find out the optimal combination of this where I need to stop how many replicates I will consider in the experimentation considering the cost like that. So, in this case and if you can collect this data randomize the data and collect the experimented results over here what will happen is that then ANOVA analysis becomes easier and it will show you whether when I change the levels this will show you a value will tell that there may be if there is significant in that case it will indicate maybe 5 is different from 10 or maybe 10 is different from 15 the mean value of Y CTQ 10 is different from 15 or 15 is different from at least there are two levels when I change from that level to the other level what is happening the mean of the CTQ is drastically changing that means significantly changing basically not drastically we can say significantly statistically statistical significance exist between the two levels like that. So, they are different statistically basically. So, that will be the conclusion but which level ANOVA will not tell you from which level to which level this has happened basically it will say any two levels are different. So, that will be concluded based on these F values or P values that you generate over here. So, MINITAB will generate P values and based on that we will conclude. So, we will continue discussion of this ANOVA analysis further to understand more about ANOVA analysis in experimentation. So, and how to implement that in MINITAB in our next session. So, thank you for listening and we will stop over here and we will start from the ANOVA next time again. Thank you.


So in subciting we talk a lot about reading speed and you already told us in the past like what sort of reading speeds can be too fast and uncomfortable for viewers. There's also I think this assumption in the subtitling world that especially in those countries where conversation is a big thing and for those subtitles who think conversation is very important. So we condense the text. We shorten the subtitle not only for people to be able to read the subtitles in time, read all the text in time but also on the assumption that we want to give them time to look at the images to see what is actually happening in the film. Do we know from research how much of people's attention is on the images versus the subtitles or could we give like advice to people what would be the ideal ratio? I'm sensing that might be impossible but is there anything we know about that? Yes, so most the vast majority of tracking studies that I have looked into have found that people spend about 30 to 40 percent of the time when subtitles are displayed looking at the subtitles and the rest would be spent on the image. The important thing we need to remember and there is a trend and this eye tracking evidence to show this that the higher the reading speed of the subtitles the less time viewers will have to watch the images and the more time they will spend on reading the subtitles. However, I have not seen any evidence to prove that when subtitles reach the speed of I don't know 180 or 200 words per minute viewers will spend as much as 80 percent of the time on the subtitles. So I think that's a little bit of an exaggeration and I haven't seen any evidence for this. I've seen this around so I just wanted to clear that. I have personally not seen any evidence for this but of course there is a trend with higher speeds of people spending more time reading the subtitles at the cost of the images. So it's used to one of the big questions in the subtitles that hasn't been answered yet at least not with a lot of rigor. So perhaps we are hoping that your researchers will provide us with this answer. No, I don't think so. I don't think it's possible to answer because it all depends on the film, on the viewers, on the context, on what's going on in the screen and what is actually there in the text of the subtitles. So there is if you're looking for a nice formula that you can apply everywhere, that if your subtitles are displayed at 140 words per minute then viewers will spend I don't know 50 percent of the time on subtitles versus the images and with 200 words per minute 80 percent. I don't think that's the case. So sorry. I wonder if perhaps that's one of the issues with communicating results of research through a wider community that research doesn't usually give us nice easy answers and provides easy and clear formulas to people that people expect. That's true. We would all love to have an easy answer, one reading speed threshold, some universal rules that would be applied everywhere but I'm sorry to say I don't think that's the case.


Hi, it's great to see you. My name is Miss Kimberly, and I'm a librarian for the San Francisco Public Library at the Merced Branch. Here's a simple rhyme called, Here is a beehive. Here is a beehive, but hidden inside where no one can see. Watch as we see them fly out of the hive. Help me count. One! Bzzz! Do this rhyme with your hidden inside where no one can see. Watch as we see them fly out of the hive. Help me count. One! Bzzz! Bzzz! Bzzz! Bzzz! Bzzz! Bzzz! Bzzz! Bzzz! Bzzz!


What's going on everyone? Sam here with Leighton Sports Guards with two boxes of 2021 Top Star Wars Bounty Hunter hobby for Matthew A. So good luck here Matthew. See what we got here. I like Crown a lot. I will be honest, it's a little bit tough if you don't hit a kaboom and your jersey and auto aren't great. Checklist is a little bit bigger in that so like not a ton of great autos outside of like the big rookies. There's a coming. The Vets like, like Luca has silhouettes. Like we pulled a gold out of 10 on the least day. So it's very boomer bust, but when it's like when it's good, it's really good. But when it's bad, it can be like kind of tough too. We've got bounty is zero the hot. That is purple 20 out of 50. These cards are so cool. So I love these right here. Nice one there. Congrats on that one Matthew. That's like with the purple, purple color match right there. Oh yeah, like you get the only shot you can get kabooms is that a crown royale for basketball. So I mean that makes it a very desirable product in that sense. And you get kabooms generally one per case. I don't think I've I haven't seen one without any and I don't think I've seen one with two. So it's pretty like pretty straightforward to one per case, which is nice. Which is the way it should be. Yeah, there are some really cool cards. I mean you get I think it breaks down to get four base four or five base one Jersey one auto one bronze ice and then two number at the back. That's a purple le 37 18 out of 75. I do enjoy ripping crown basketball though like when it released and we're doing case cases of it was fun. The green embo green 10 out of 99. Nice one there to cool looking part blue Han Solo nice one there. Prism so better than select. Yes and no I mean like man that's a that's a tough question because there's so many factors that go into it too. Like you get more hits in select so like the low numbered color parallels and prisms sell better than the low numbered color parallels and select. So I think I think a gold vinyl Mac Jones would outsell a green Mac Jones. Gold vinyl out of prison to five. Or like I'd say a gold prism will still outsell a select gold. But like now that then you have to throw in you get our PAs in every box out of select the RPA sell a little bit better. A lot of times we've got auto here is governor a Rinda price out of the animated series. That's Mary Elizabeth McGlynn. I feel like it's just with select versus prism. It's such a card by card basis. And if a lot of it depends on personal people's personal like preferences too. Yeah I would say prisms a little bit more sought after for sure. But like prisms also such like a color product versus select like the odd I feel like the auto is out of select or more sought after the auto is out of prism. Because like a lot of times you'll see like this. I don't know how this really makes sense. But like the gold auto like the gold base will outsold the goal will outsell the goal. Black Friday sold more than the black Friday auto which is crazy. I mean I get it because it's like the true. Yeah and people really don't like stickers. Yeah that's also a very good point. Also a very good point. But I feel like great products like this. Oh yeah no they're both fantastic. I love both like I mean there's those are like those are legitimate staples. Yeah for sure. Frog lady that's a green Toro Caliqin that is a 66 out of 150. I mean personally I would get fast break over each two. I mean it depends on your budget to box this like if you want to get a cheaper rip like select each two is definitely the way to go. Got boss on the purple 60 out of 99. But then like going back to the out the outselling of things like I feel like I could be very wrong in this. I don't I don't have like I'm gonna be 100% honest with everybody. I don't have numbers to back this up. I don't know I haven't looked it up. This is just what I feel seems to be the truth. The truth is that beat like true rookies non-autoed will sell better in prism. We've got Ketsu Anyo red 22 out of 50. Nice. Nice hit for you there. But I feel like the in select like the autos will outsell the the autos like a gold auto will outsell a gold rookie. You know what I mean like a gold auto outsell a gold field level. Again, I could be wrong on that. I have no idea. I have no numbers to back that up. I'm not a bitter out on a lot of high end select because I can't afford it. And H2 doesn't have. I think it does because you can get disco field level out of it. Yeah. I mean the only thing with each two is like you get you get six prisms per box out of four packs or whatever it is. But you're not guaranteed a numbered card out of it either. They could literally be six disco like disco silvers. Yeah. Non-numbered exactly.  Not scary, but like I don't love that. I think you should be guaranteed like one or two colors. But again, like you have shots of gold. You have shots of green shots of black finite. It's like the good thing about select H2 too is like it's a whole another pool of like, you know, stuff you're not going to get out of hobby.   I think that's a good. That's a little bit of a good selling point for hybrid. Auto is going to be again governor a shinda pray or a rinda price. Excuse me. This time it's blue though. That is a blue 33 out of 99. Nice one there. And I just love her star wars stuff. Like I am. I freak out when someone orders masterware. It's like my favorite thing in the world. Oh gosh. So much fun. And guys, if you want personals, I'm going to link the like it in chat. Q is getting very short now. I think we're down to like four. Yeah. Four orders in Q after this. Yes. Yes. Yep. The discos are exclusive to H2. That is a purple boba fat. Nice. 53 out of 99. Nice one there for you. Matthew. What's up KJ? How you doing buddy? Yeah.  You know what I mean? And then your autos and RPAs and stuff tend to fall like one a case. So it's a little bit more of like you're really kind of going in with the mindset. You're not going to pull an auto. You want to get some color. Green box this time. That is 56 out of 99 on the box. Lego Star Wars legend right there. Love that guy. I remember I was like always trying to save up for the three bounty hunters. It was him, Greedo and IG88. Yeah. Yeah. Greedo's dead with two. Greedo's sick. Yeah. He gets murdered in the first movie. Yeah. Yeah. They don't give you that anymore. No they do not. They do not. Purple Lando. There you go. That is 26 out of 75. Lando Calrissian. Cloud City legend. Bass in there. I would say we've got a Merlin three tier, one Bundesliga's three conical racing. I would say like a half an hour, 45 minutes, Jeremy. Got Chewbacca on the bounty card.  That's nasty. Would you say, I would say two up probably. Just because I'm worried they're going to hold out Herbert for the game. Yeah no problem Jeremy. Yeah, feel free to jump in grab something man. Always fun ripping for you. Jeremy's always buying some stuff. Good old Jeremy Z. What's it called? Chewbacca's pretty nasty. Yeah I would, I think it's just safer to go to a like, you're going to be a lot less stressed before football starts, you know. Ooh. Die cut for long. Case hit. Nice man. That's so sick. These are cool dude. It's like the Vader mask. That's awesome. I've never seen one of these. So cool. Die cut. Case hit. Heck yeah dude. For long. I bet the Bobas must be money out of this. Dylan he's going to sleeve it. Pesitents to play the bill of defense. Yes. Well the bills have a lot of injuries. Yeah bill of secondary is like, definitely like, it's marred with injury for sure. Like a hideout for the year. Yeah I know. I didn't get enough attention in my opinion and it showed up. He's like an elite safety. Yeah for sure. And I remember I just like pulled up my phone and it was like a hide out for the year. I'm like wow. That should have had some legitimate attention on it. Yeah. More people should have got attention. Yeah. I mean granted more people were obviously, and with good reason we're worried about being the corner of her neck.  So like thank god that guy's okay. So I think that's the reason you get a ton of coverage. Got a green Han Solo. Nice. 46 out of 150. There you go. That's on that one. Exactly hide in our corners out for the year. Yeah plus trade whites on IR until like the gate or whatever it is. So won't be seeing any trade whites. That secondary kind of stinks. Dengar. 26 out of 35 on the purple. Nice. A lot of nice color coming out of this so far. After this break you want to throw the TV on? Yeah, I got you. I don't want to have red zones. We've got to pick which one of the games we want to watch. Base. Hopefully we're even patriots. I can't imagine it's going to be.  That is going to do it for your break there. Matthew congrats on the hits.  I have not seen one of those. So that was definitely a very fun pull. Again, we will send those right out to you. Thanks again buddy.


You may have heard your teacher referring to thesis statements. The might have said, what's your thesis statement within your essay that you've submitted or make sure you include a thesis statement.  What's a thesis? Why must you make a statement? So what I wanted to do within this video is to show you how to craft a thesis statement to explain to you literally what a thesis statement means, but equally to present you a framework that you can use for every single essay when it comes to thesis statements. So let's first begin by talking about what exactly is a thesis statement. Now, remember that a thesis statement is something very, very basic and it comes in your introduction. A thesis statement essentially sums up your main points within your essay. Now remember, when it comes to thesis statements, these apply to literature set text as opposed to language, okay? So when you're writing about a literature text, you basically begin by summing up your main points within your introduction. And then your thesis statement then comes in at the end of the introduction, where you basically sum up exactly what you're going to discuss. Now, one of the reasons why thesis statements are really important, especially within your essay where you're summing up from your introduction and from the outset of your essay, exactly what you're going to discuss is firstly because it means that your essay starts off really, really, really strong, okay? Now, remember, first impressions really count even with essays, okay? We think about first impressions when we meet people, but equally when your teacher or your examiner is reading your essay from the opening and from the introduction, if you show that you have a very strong grasp of exactly what you're going to talk about in relation to the question, that means that they already are on your side. You're already winning them over from the introduction because they can see, okay, this person has a really strong handle and a strong grasp of what they're talking about. However, the second reason why you want to use a thesis statement in your literature essay is it also makes your arguments quite clear because you're basically summing up your main points in a really concise introduction. This is what I'm going to talk about. This is the key themes and the context that I'm going to bring up within the body of the essay. And of course, to do this, you need to have planned a little bit in advance to know exactly what you're going to talk about, okay? So it makes your points quite clear both to your teacher and your examiner, but equally to yourself. Now, what I want to present to you is literally the perfect template you can use when writing any thesis statement, okay? So as I've mentioned, this is the template that I'd like to present to you to use in your thesis statement. And I'm going to show you how to apply this template when writing about a text called Macbeth for William Shakespeare. But to be honest, this template can be used for any text. So let's first have a look at this template, okay? So a thesis statement, you can write it in exactly this way. In name of the text, we're invited to see keywords from the question as throughout the text, include your perspective and ideas. Arguably, author's name's intention was to then you finish off with your view, context and theme. So I'm going to go over the framework one last time. In text, we're invited to see keywords as throughout the text, your perspective and ideas. Arguably, author's name's intention was to your view, context and or theme, okay? So that's basically the template when it comes to writing out your thesis statement. Now, as I mentioned, I'm going to give you an example taken from a question on Macbeth. But honestly, as long as you know the keywords within the question and the text that you're answering, you can literally apply this framework to any text. So let's have a look at this example that I've taken from Macbeth by Shakespeare. So the question asks, how does Shakespeare present Macbeth and Lady Macbeth's relationship? So of course, when I'm looking at this question, firstly, what I need to do is to firstly be clear on the keywords. What are the keywords? What is the central focus of this question? There are three keywords within this question. The first keyword is Macbeth. So I need to make sure I'm talking about Macbeth. The second keyword is Lady Macbeth. So of course, I'm equally need to make sure that I'm talking about Lady Macbeth. And the final keyword is their relationship. That's the third keyword, which will of course go in this part of my thesis statement. So as I mentioned, as you can see here, I have crafted a response applying this question and also applying this thesis statement framework to this particular question. OK, so I'm going to read you through it and then I'll break it down how I have included all these different elements from my thesis statement template. OK, so let's have a look. How does Shakespeare present Macbeth and Lady Macbeth's relationship? In Macbeth, we are invited to see Lady Macbeth and Macbeth's relationship evolve as throughout the text, Macbeth and Lady Macbeth's relationship shifts from being intimate and trusting to distant and detached. That's the opening part of my thesis statement. Where am I? Arguably, Shakespeare's intention was to illustrate how corrupting their ambition was, given the both conspired to violate divine right of kings by committing regicide. Shakespeare wanted to use the breakdown of their relationship to reveal the corrupting effects of ambition, which wreaked havoc and chaos in their marriage, as well as Scotland. OK, so that's my thesis statement relating to my introduction. If I were to write about how Shakespeare presents the relationship between Macbeth and Lady Macbeth in brief, what I've basically said in lots of words in terms of my main points is that Shakespeare uses their relationship to represent how terrible ambition is. The relationship goes from being really close to being distant because what this is illustrating is firstly contextually the violated divine right of kings and caused chaos, but their ambition theme caused them not only to cause chaos in Scotland, but equally this wreaked chaos in their own relationship. That's how it changed. OK, so let's quickly dissect how I've included the different bits in my thesis statement. So I've began by in Macbeth in this name of the text. We are invited to see. So now these are the keywords from my question. We're invited to see Lady Macbeth and Macbeth's relationship evolve. So I'm saying that it changes, it evolves, right? So that's my keywords. And throughout the text, next part, which is my perspective and ideas where I sum it up really quickly, Macbeth and Lady Macbeth's relationship shifts from being intimate and trusting to distant and detached. That's my general and overall perspective and ideas. However, I'm still not done with my thesis statement because I still need to include these other elements. Arguably. Author's name, Shakespeare's intention was to illustrate. And now here I'm going to add my view and context and theme. And you're going to see that this is what takes up the bulk of your thesis statement. OK, so your view, your context and your theme point is now what's going to take up the latter half of your thesis statement, which is towards the end of your introduction. OK, so Shakespeare's intention was to illustrate how corrupting the ambition was, given the both conspired to violate divine right of kings, which is context. OK, the commitment of Regicide is divine right of kings by committing Regicide. Shakespeare wanted to use the breakdown of their relationship to reveal the corrupting effects of ambition. So now this is theme that I'm relating to, which wreaked havoc and chaos in the marriage, as well as Scotland. OK, so obviously this is a fairly wordy introduction. And of course, remember, your thesis statement does need to be a little bit wordy. However, it usually tends to come at the end of your introduction. So your opening introduction is where you generally broadly open up what you're going to discuss. However, it's more towards the end of the introduction. That's where you really delve into your viewpoints, your context and themes, meaning that you start off quite strong. And most importantly, you make your arguments quite clear within your answer from the opening of your essay to both yourself and also your teachers and examiners. So that's really it when it comes to thesis statement. I would like to suggest literally just use this framework and use it to apply to other essays as part of your approach to thesis statements. Thanks so much for listening.


Hello friends, so welcome again to another session on theorems of triangles and its angles Now we have taken one corollary of the previous angles and property which we saw in the previous session the corollary says if the bisectors of angles ABC and ACB of a triangle ABC need at a point B Okay, so you can see bisectors of angle ABC Which is BD and bisector of angle ACB which is CD meet at point D then angle BDC, okay, BDC is this angle you can see that is given by beta is equal to 90 degrees plus half angle B a AC which is given as alpha So the corollary is given here. So beta is 90 degree plus half angle alpha take 30 seconds pause and understand the figure After that what we'll do is we will try to validate this and in different configuration of the same triangle will try to validate Now indeed beta, which is angle BDC is equal to 90 degrees plus half angle alpha, which is BAC Okay, so first let's validate it and then in the later part, let's try to prove this So what I'm going to do is I'm going to change the configuration of triangle ABC and In all the cases in all situations, we must have this particular relation always true Okay, so I'm going to change the position of a so here I go So you can see I am changing and I'm now here at this point So again, you can see beta is 90 degrees plus half angle alpha in this case alpha is 60.41 degrees So half of 60.41 plus 90 is 120.21 degrees. Okay, so Wherever I take B the relation always holds. There is nowhere Where it doesn't hold is it I can change the location of B as well see I'm changing the location of B as well But then in that case also this angle is 90 degree plus twice this angle Isn't it? So if I change C as well The relation is going to be true. So at any configuration you can see you can pause the video and see that This particular relationship always holds now we will look at the proof of this Corollary what is a corollary corollary is nothing but Statement in mathematics drawn from a particular theorem. So that's a corollary. Okay, so next let's prove this particular So here is yet another theorem which says that if the bisectors of triangle ABC and ACB of triangle ABC meet at the point B then Angle BDC is equal to 90 degrees plus half angle BAC Okay, I simply read the statement. Let us now try and understand what this means We just saw the validation by the way in the previous part of this video where in GeoGibra We established this particular term that is indeed if you take an triangle ABC and This angle or BD. Let's say is the divisor or BD is the Angle bisector of angle B and CD is angle bisector of angle C. So if this angle is Alpha This angle is beta this angle also is alpha and This angle is also beta. That is what is the meaning of angle bisectors. Now we had just Saw in the previous sessions angle some properties. So we are going to use that property to prove this so angle BDC What is BDC? So let me call it gamma BDC is gamma and let's say this angle is delta So don't get confused if I'm using such Greek letters. So alpha beta gamma delta So let's see the proof now So how do we do this proof? first of all the The customary step given what is given BD and CD are Angle bisectors Angle bisectors of what? angle ABC and Sorry, I have to write angle ABC So this is angle ABC and Angle ACD Correct and the word respectively Respectively why because of this one-on-one mapping that is ABC's bisector is BD And ACD is bisector is CD Okay, so to prove To prove Angle BDC is equal to 90 degrees plus half Angle BAC Correct or BDC is or you have to prove what gamma is equal to 90 degrees Plus half Delta This is what we have to prove. Let's try and prove now We don't need a particular construction here. So you can say in So I'm saying in triangle in triangle ABC in triangle ABC, what can I say? Delta The angle A that is Plus twice angle alpha Plus twice angle beta. So three angles put together Delta twice alpha is you can see this is twice alpha Angle B and twice beta is angle C. No problem in that This is how much 180 degrees and what is the reason behind my writing such things? Angle some Property of a triangle correct Isn't it now this let it be equation number one Next is I'm writing here so that everything is in one frame second. I can write in a Attention to triangle BDC BDC so same angle some property will hold here as well. So gamma plus Alpha plus beta is equal to 180 degrees Isn't it? Yeah, what is this again ASP? I'm writing in short form ASP angle some property of a triangle and I can do some manipulation over here. What manipulation can I do? I can just multiply this by two So multiplying this whole equation by two Why did I do this? You will come to know Just in a while Two alpha plus two beta is equal to three sixty degrees Is it it? Let it be two Okay, now we will do one operation. What is that? Either or you can say two alpha plus two beta. Let's say what is it? 360 degrees minus two gamma Is it it? right and from one From one what can we say? Two alpha plus two beta is equal to 180 degrees minus delta right So this is let's say three This is let's say four So you can say from three and four the LHS of three and four Are same if you see correct. So we can equate the RHS as well So 360 degrees minus two gamma Is equal to 180 degrees minus delta Is it it? So If I simplify I will get Two gamma Is equal to 360 degrees minus 180 degrees plus delta Okay now this is Nothing but two gamma is equal to 180 degrees Plus delta right so what will be gamma guys? So i'm going to multiply this equation by half or divide by two whichever way you want to say it and this is equal to gamma Is equal to 90 degrees plus delta by two correct? And this is where gamma is equal to 90 degree plus delta by two and this is what we needed to prove check Right, this is what we achieved. Okay, so please remember this corollary as well