For those of you just joining the room, welcome. We're talking about cities and data, and we have up next is Kate Rabinowitz. She's the founder of DataLens DC, where she analyzes and visualizes data to tell stories about Washington DC. She also works with clients to bring data to life through data science and visualization. She's the co-captain of Code for DC, a volunteer civic hacking group, the co-founder of Tech Lady Hackathon, an event series promoting women in DC tech, and she's a recipient of the 2016 Technologist of the Year Award and 2017 DC Femtex Data Scientist Award. So she's pretty awesome, and this is gonna be a fun talk. So welcome, Kate Rabinowitz. Thank you. Hey, everyone. We're gonna be talking about open data and cities today. So let's jump right in, starting with a definition slide of what is open data? So open data is data that is freely and ideally easily accessible, with little to no restriction in terms of how you use the data, what you do with it, if and how you go on to share it. Specifically today, we're gonna be talking about government open data, and it's important to remember that as citizens, we are owners of the government, and as such, we have a right to the data that it creates in almost all circumstances. And this is important because government data is very valuable in terms of social and economic impact. It is awesome, especially when we look at what it can do for cities. So with open data for cities, we can answer questions about our cities, we can spread conversations, we can uncover and solve puzzles, we can create change. Let's go through a few use cases to see what that looks like in practice. So these are a series of maps that I created for my city, Washington, DC, and it looks at how different neighborhoods in the district have changed across the past decade by race, income, and age. The darker, the blue, the whiter, wealthier, and younger that neighborhood has become. These characteristics are often associated with gentrification. When we bring data to these discussions, we can get a better idea of what gentrification looks like and where it is happening. Within these three maps, there's one neighborhood that is dark blue across every single map. I'm gonna move, I apologize. This neighborhood is Navy Yard, and in the past decade, Navy Yard has had a huge influx of new residents, generally whiter and wealthier than long-term residents. It has had a lot of new construction, new apartment buildings, even a new baseball stadium. With open data, we can identify these kind of hotspots of gentrification, see what it looks like, and start to think about how we can support the communities that are affected by it. Open data can also help us understand a social issue within our city from a different perspective. So this is the Million Dollar Blocks Project in Chicago from Data Made Co. And what they're doing here is they're looking at crime in the city of Chicago from a different perspective. Typically when we look at crime, we think about a map that has points on it of where a crime has occurred. And this kind of perpetuates a notion of crime as an individual and isolated act. What Data Made Co. has done here is they've visualized data on how much money the government is spending per block in Chicago to incarcerate residents that would have otherwise lived on that block. So we're flipping the perspective here and in doing so, getting a bit more to the institutional causes and societal costs of incarceration, we can start to see these kind of heavy concentrations of where that money is being spent. The kind of lack of people in that neighborhood as a result of incarceration. And on some blocks, literally a million dollars being spent. And we can think about that in juxtaposition to how much the government is spending on social services within the neighborhood. Do you have a question? Sorry, I should put a space there. Okay. So open data can also help improve communities. This is an example from Living Lots NYC from 596 acres. And they've used open data to identify vacant lots within New York City. There are hundreds of vacant lot spaces in New York City and they were able to identify the vacant lots and then who owns those vacant lots. They created resources for community leaders to then work towards converting that into either like a park or a community garden or whatever the community and the lot owner came to an agreement on. I think at this point, there have been about 80 acres converted, which for New York City is actually a lot of space, but using open data, they were able to systematically identify an issue at the city level and then bring that information and resources to the community level to help fix that problem. Open data can also help hold government accountable. So ideally government is always working in our best interests. Transparency and open data are really helpful in providing checks on that to make sure that that is the case. IQuant New York was playing around with parking ticket data and found that the city police department had been systematically ticketing legally parked cars to the tune of millions of dollars of fines a year. So there was at one point, a parking ticket category that was totally legitimate and then it changed. It was no longer a parking ticket, but the police continued to hand that out. And in this case, once this became public, the police department did remedy this in terms of at least going forward, they are not handing out these parking tickets anymore. So these are a kind of handful of examples of what we can use open data for in our cities and a next question might be, where can I find this open data? And there are a few different spots. The kind of like main website for federal data is going to be data.gov. And that's gonna have your headline, economic, social, business demographic data. There are nearly 200,000 data sets on data.gov. Your city also collects a lot of data. And if you live in a major or a mid-size and in some case sometimes even small city, at this point they likely have an open data portal. And there will be a wide range of data on that portal, in some cases, from property tax data to public transportation data, to crime data, to demographic data. And all right, I'm sorry. I, the examples that I gave you, I think are really excellent use cases for what individuals can do with open data. And I think that's awesome and exciting. But when I start to talk about open data in practice, I just, I have to be real with you guys. In practice, working with open data is kind of terrible. And this is an emotional journey that I've been on. I think many open data practitioners feel the same way. It is weird to say this at a pew right now. But the promise of open data is really awesome. In practice, working with open data has many, many challenges. Some of you were maybe rolling your eyes when I was saying that data.gov has nearly 200,000 data sets and that is rightfully so because a number of data sets is a terrible metric for the success of open data. Let's use data.gov as an example. So of the nearly 200,000 data sets, two-thirds are geospatial. The most common tag on data.gov is oceans. So about a third of the data sets on data.gov are about oceans. When I go to my open data portal for information about my country, I typically mean like inside the country and not the ocean surrounding the country. So when you go to an open data portal and you see that highlight number, it might not necessarily be what you would consider high-value data sets. It also might not be in a format that is particularly friendly. This is less true for at the city open data portal level, but for the federal government, PDF is number two in terms of data format type. PDF swear data goes to die. The friendliest of data formats, CSVs is not even in the top five. Number of data sets is also a bad metric because it can so easily be manipulated. I do not think this was their intention when they did this, but if I look at what I would consider one data set on the DC Open Government Portal, moving violations, it is actually dozens of data sets because they have broken it into monthly moving violation data sets. So when you see that top headline number of number of open data sets, it is often a bit more deflating as you peel back the layers. It might not be the data that you were hoping for. It might not be in the easiest format. So if you are using or thinking about using open data for a city, you should have FOIA as part of your toolbox and you should also consider advocating for more open data because there is a lot of work to be done. But let's say you have your open data through the Open Data Portal. That is success number one. Working with that data is going to be challenging because open data can be very messy. The way that we're talking about using open data today in many cases was not the original reason that it was collected. So it can lack the infrastructure or it has so until very recently for accurate, complete and clean open data reporting, there are still city agencies that collect this data by fax. In many cases, the system where they hold the data is entirely different from the system that is their open data portal. So translating between these two things can be harder and more manual than you would like. Working with open data almost always has more free form text than you want it to. And this goes back to data analysis not being the original reason for collecting something like business permits. Data standards are not particularly common. On the upside, if you are working with open data for your city and you clean it, you might be the first person to ever get a clean perspective on that data. In cleaning data though, we make decisions. And this leads to my next point which is that open data, even when clean, is far from fact because there are so many opinions that go into any data really being made. So data is shaped by the people around it. We should consider it just as bias and imperfect as the people who create it. Open data is sometimes talked about as a kind of absolute truth or a kind of catch-all solution. It is not, it is a means. And when we talk about and use open data, we have to put it into the context of the environment that it's operating in. So open data is complicated and let's talk a little bit about what that looks like. When you're working with open data, there are always some questions and checks you should be doing really when you're working with any data. The first is asking who collected this data and how did they collect it. This is kind of an involved example here so let's take a sec to walk through it. In DC, as with many cities, there is a Vision Zero initiative to make streets safer for everyone. There is an app in DC and many other cities where citizens can report issues that they have whether it's a cracked sidewalk or a blocked bike lane or a speeding car. This in particular is pedestrian issues. So that's what we see on your left and what we see on the right are crashes that involve pedestrians. So this is not, neither is a perfect corollary for pedestrian safety, but the problem with the one on the left which is data collected by people logging issues into their apps is that you are sub-setting who is going to take part in that from the start because not only does a person need a phone or an internet connection or an app, that person has to know about the initiative, take the time to actually care about the initiative and think that their government is going to effectively respond to their issue. And this sub-set is typically a wealthier sub-set than the general population. So when you're collecting data through a website or an app, you're not going to hear everyone's voices and it's important to consider who you're hearing more of and who you're hearing less of. Here I have circled one particular neighborhood because it's where I live, Capitol Hill, for comparison. On the left you'll see complaints and if you look at complaints surrounding pedestrian issues, you would think that Capitol Hill was like a pedestrian death zone because there is just so much heat going on there. I live there and I can tell you that it is like a walker's paradise. I can also tell you that Capitol Hill has probably like their PTAs are probably the most involved of like anywhere in the city. So when you ask people their opinion through something like an app, you're going to get an opinion that they think a car was speeding but you're also going to get something like how involved that neighborhood would be in a PTA meeting because when we look conversely at pedestrian involved crashes on the right, we see that like Capitol Hill, it's actually, it doesn't seem that bad. So it's important to put your data in context in terms of who's collecting it and how they are collecting it. Once that data is collected, there can be a number of decisions made about what to do with the data. And often when you're working with open data, you're going to find anomalies. And so this is a line chart of when homes were built in Washington, DC based on open data. So if I was just like running with this, I'd be like, wow, 1900 was a boom year. Can I commission a historical study on what happened at the turn of the century in our nation's capital? But that's not at all what happened. What happened is that when the city doesn't know the year that a home was built, but it's like a pretty old home, they just tag it as 1900. So this is an example of an anomaly in the data being entirely by design and not reflective of reality. Policy also lives in your data. So here's another anomaly. This is parking tickets in DC and they are parking tickets specific to inspection stickers. So if your inspection has expired, if you fail to report for an inspection, DC is very small and there's a lot of like interaction between DC, Maryland and Virginia. So looking at this graph, I'm like, okay, DC, Virginia, like roughly same levels of parking tickets that makes sense, like what's up with Maryland? Once again, if I was gonna run with this, I'd be like, those Maryland drivers are fantastic. Let me commission a study, let me data science how everyone can be a Maryland driver. Maryland drivers are not fantastic. What's actually happening here is that in Maryland, you only get an inspection once and then you never need an inspection again. So because of that, you can never be ticketed for having an expired inspection sticker. So policy lives in your data and when you're working with your data, you have to consider the legal and environmental factors around it. Data also lives in society and it's really important when working with data that you put it into that context. This is the racial dot project out of University of Virginia and essentially every dot corresponds to the race of a person. This is looking at Detroit, you can also look at it nationally. Looking at this map, there are some unnatural things going on so that line of separation up top and then once again, this weird loop-in of blue, we see that it's highly segregated and if you were to leave it at that and just let the reader come to their own conclusions, in my opinion, you're not doing enough of putting the data in context. There are very specific reasons why this looks the way it does. There were policy decisions made, there was redlining, there were laws and when you visualize data like this, especially when there's people behind that data, it's important to put that data into the context of society, the laws and the decisions that we've made. So open data is awesome, at least the promise of it is. In practice, working with it is kind of terrible at times, but hopefully we can use this data, putting it in context and working with it responsibly to make better use of our cities. So let's do all the things with all the data for all of our cities, but actually don't do that at all. Only do ethical things and be mindful of the flaws in the data and also put it into context and so all the things but only the good things, please. Thank you. Thank you.


So this is on basic design principles for developers so sort of enabling developers to do a bit more design or be a bit more Adventurous About me I am I studied my name. Sorry. My name is Ricky I studied graphic design and I've been got a job as a web designer in 2007 and then I've Learn front-end dev and PHP just sort of on the job and and so now I sort of consider myself a front-end developer more than a designer I don't really design anymore And I've been a Drupal user since 2009. I have one Drupal module up proud of that So I just wanted to know a bit about you how many front-end developers do we have in the room? Yep, okay, and back-end developers Okay, cool Any content editors or just non developer people? Yeah, cool. Good mix. All right So why learn about design Essentially we want to be able to communicate better with designers and to have a smoother sort of working relationship together As well as being able to educate them about some of the responsive pitfalls that if anyone in words in the last talk Milly's talk you would have heard about them and Then sometimes you you'll quite often be handed in complete designs by Designers whether their budgets run out or they just haven't considered all of the pages Or the features you're doing. There's maybe a new feature to put into a site So in in that case you should be able to ideally be able to do some of it yourself based on the other designs that you've got and then Just I hopefully save a bit of time have a have a go yourself. Yeah So the start of it is typography I think typography is the most important part of web design All websites are type essentially. It's all information So optimizing that type and making it really readable and really accessible to people is a big part of design Fonts we've all got great web fonts to use now Ideally you can just follow Existing branding when you when you're coming up with these things you shouldn't need to choose new fonts from scratch You might be finding a web font that matches a print font or something like that. So just and Then just seeing which fonts you should use in your site. So here I've got the different types of fonts We've got so sans serif fonts are generally modern clean fonts Always good for body copy because they're really good at a small size Serif fonts are sort of a more classic look and they're really good for headings They can be a bit harder to read at small sizes But you could if your body copy was like 16 pixels or up you could use a serif font Handwritten fonts are like really decorative and Should just be used for headings really and in certain use cases same with script fonts that they're much harder to read at small sizes And then monospace fonts, which is just equal character width. It's very tacky font Easy to read for developers because we're used to looking at them Shouldn't use more than three fonts in in a site or in a design This first blue example here is just two fonts and that's probably the easiest just have two different fonts You can you can do three fonts in this case I think it's really good to have three fonts when there's like you've got a serif font for your body copy you've got a Decorative font for your headings and then you could use a sans serif for smaller fonts like a meta Sort of information like dates and stuff or or UI labels Sans serif fonts are really good for them So that's a good example of having three different fonts in us in a site Star signs for fonts and you just it's hard to do It's really hard to do even for a really experienced designers to make four different fonts look good in the site So it's you just don't need to worry about it just avoid doing it You Can do a lot with the weights and and sizes of different fonts rather than needing a different font family altogether You can just create that same hierarchy and that differentiation through higher through font sizes and weights So you can see how I've just got four different font sizes and two different weights So it's not hard to do Some things that designers to sort of design a vocabulary letting equals line height to To them and us so it's sort of again the communication between you so you understand what each other are saying Kearning is the same thing as letter spacing for us type setting this stuff is is a big part of what a traditional print designer Spends a lot of their time on it's it's very important to them And it's not necessarily as applicable on the web, but there are some cases where it's relevant Orphans are as it says a single word on its own line at the end of a sentence or paragraph so paragraph in there being the orphan and That's yeah, so that that one's a really hard one to control on a responsive website, but places where it might be worth Focusing on that is in like a positioning statement or One sort of thing that you do have a bit more control over and it's less likely to change And you can at least make it type set it well for the major break points of of a design The last one's really for content editors. It's just that people skim So use your heading weights that you've got all set up and and break break up your paragraphs So it's really easy to read So last one is CPL which is characters per line and it's sort of there's a there's an ideal number of characters or words for each sort of the width of column of your text and it really helps with readability So you can see this first example. It's too short. It's Disjointed to read and it's just sort of just chunky a bit and then this other one is really too long So by the time they get to the end of that line there I has to go all the way back to the beginning and They'll quite often lose the line that they were on what so what was the next line by the time they get back So that's a so there's just sort of a middle point in between those two is what you what you're aiming for and font size it relates to CPL as well so you can see this Second line here if that was a big font size like I've got up the top it would be fine But it's just that it's so small and it's such a long line. It's hard to read These guys personified.com Four slash typography. That's a really great calculator for this so you can either just put in The column width that you that you've got and it'll tell you what font size To use to have that optimal sort of size or you can just put in the font size And it'll tell you what's a good column width to use And it also goes into other heading levels as well So you can have your base body size and then using the golden ratio It'll tell you what a good heading sizes as well to use so you don't need to make it up. It's all online Space and proximity refers to White space vertical rhythm and the proximity of elements so it's all sort of relationships between things White space isn't necessarily white. It's just empty space. So it's it's a term designers use And it can be confusing to people they sort of think it's You you say you want a really white lots of white space and then someone will think that you're just wanting them to have a really white website It's not the same thing It's used to break up the site into digestible chunks So it's sort of a really good example is your Your main column of text from your side column and you can have white space in between those to differentiate them and separate them You could use a line to differentiate them in in your design, but that just adds noise You often don't need it. You just add a bit more white space and then it's simpler and easier to read A lack of white space is cheap. It is intentionally used to make something look cheaper So you'll get it in those Catalogs that are crammed full of stuff and they're they're a low price point product and that's what is That's what you use lack of white space for And then on the flip side lots of white spaces luxury. It's like I Can afford to waste this real estate It's fine So if you want your product to look really expensive then use lots of white space Vertical rhythm is quite a big thing and I'm not going to go into it too much, but it's basically the consistent pattern for the reader so it's the like the lines I suppose um if You had like two columns of text Next to each other and then if you had a good vertical rhythm It wouldn't matter how many words were in each column or how many lines of text They were all where the breakpoints were in those columns in those paragraphs. They would always still line up Next to each other. So just have a consistent line. That's your vertical rhythm It's quite a big thing and you can read a lot about it online Proximity of elements is the relationship between elements demonstrated by the use of white space So you can see here this date This is probably like in our side column It's some news articles and we've got a date and it's got the same amount of white space on the top as it does on the bottom And it's hard to see what news article this date might belong to in this example So you can easily fix that by adjusting the white space to to create that relationship with something and To give it proximity color Color is a really big thing. It's it's hard I suppose you all saw the blue dress that wasn't a blue dress. Yeah, so it's perceived differently by everyone and then it's also There wasn't blue dress, yeah and so it's also Exasperated by different monitors. We all have a different screen that's calibrated differently. So it's hard to have The exact color that you choose be the thing that is what's seen So and especially for people that are colorblind. Is there anyone colorblind in the room? No, okay Colorblind people see different colors to what we see The next slide is a bit offensive So these are these are really bad color combinations So sorry, I'll just go back to the first point. Follow the branding again. Just use what's already been designed if you can Yep, so these particularly bad color combinations and this is what someone that's colorblind will see so it's really sort of low contrast Really sort of they wouldn't get the message if you were using color in that sort of way and so for accessibility reasons they say To never just have color as the differentiator So if your hover states are just color then they won't necessarily be seen by people that are colorblind So they they always say to have an underline as well as a color change in those examples But you can use color To make certain things stand out from the rest of your design So if you've got a color part that like largely blue And you want everyone to see that that button on the bottom and you want everyone to click on it It could be blue. It would fit in with the design, but you could also use a contrasting color and Have it stand out a lot more against the rest of design and it's much more likely to be clicked on in that case Orange has poor accessibility It's just one of those colors that has a pretty low contrast despite what it looks like to us a lot of time And these are some sites that will help you choose color It's just to be accessible. So the first one is for choosing your whole color palette. You can basically say I want every blue color at this font size to be Triple A accessible and then it'll spit out every possible blue That you could use in your in your design and it's really cool And then the second one I use a lot to test Existing colors, so it's just it's a calculator again. You put in a hex code You put in the so the foreground and the background color and it'll tell you how accessible how much contrast that color has I'll put these slides up online Mobile design going way too quick So Mobile design is basically reducing things and increasing other things So ideally you'd want to start small and enhance as the space increases so headings and text sizes would would be Initially done to that smaller carrot CPL column width So you can have your based on your mobiles with thingies And then as it increases you can you can calculate up from that what what the bigger sizes should be up to your desktop size Buttons and links are the only things that you wouldn't that was sort of the opposite So they need to be increased on a smaller screen than on on a desktop screen and it's to allow for fat fingers Basically, so there's a big hit area for buttons and links And Apple recommends a 44 pixel by 44 pixel Sort of size so whether it's like At least 44 pixels high and then they say you can do like 30 pixels in the opposite way Just so that there's enough space And that's it I think I did that way too quick I turn that so much longer at home Yeah, lots of questions Yeah, yeah Um I suppose just repeat it for me again Yeah, like I I'm all for Sort of making it more of a Closer thing like I think designers and developers should work a lot closer together And I think managers should Encourage that really yeah, I think it's it just makes everything so much smoother like My own experience coming from a design background and then moving into development that design experience has really helped me in my job and Just made things better. I think it's a great thing and everyone should do it Yes, yep, okay, so Well, I've I've done it here obviously So there's certain sort of weights of text you can use and then having a drop shadow like I've got here is a really good tool Just to increase a bit of contrast It can be done It's just sort of it's not a one-size-fits-all thing like you have to adjust it for every background image You have to have different position of your text to be on the most clear part of the image it's a fiddly thing and And Yes, there are screen size changes. Yeah, it's much harder to do on the web But it can be done. Yeah. Yep. Yeah, things like that. Yeah Yeah, yeah Yeah, yep I actually don't but someone else might Yeah Yeah Yeah, yeah, I think it yeah paid ones Yeah Yep Yeah Yep Yep I Think they're a really good starting point for people when they're not necessarily as Experienced in in doing things from scratch. I definitely do As far as I've always done it from scratch myself, but yeah, it's Yeah, I think it is important for developers to do it from scratch at least once I mean, they might not like it and they might want to go back to their original way of doing it But I think it's a good learning curve for people to do. Yeah Exactly Yes, yeah Yeah Yeah, it is it is frustrating. Yeah, even like I say if you can speak their language You can you can explain things better to them, but it's still It depends on the person really and how how much of an ego they have I guess yeah Yeah, yeah Yeah Yeah, yeah, and then redo it. Yeah. Yeah Mmm early break then I guess


Keynes and Hayek head-to-head and Just to let you know what's coming is that I'm going to start out with with the Keynesian Model that you see in some of the textbooks and so on and then eventually morph from there to the Austrian view and Note the changes you have to make to get to the Austrian view and see if you see any Anything wrong with those changes, okay? We see what's going on here Okay, here they are Keynes and Hayek head-to-head. It's not really too hard to put them that way There they go And just a brief characterization of both frameworks Keynes vision of the economy suggests a circular flow framework in which earning and spending are Brought into balance by changes in the level of employment Not by changes in prices or wages or interest rate, but by changes in the level of employment Hayek's vision of the economy Suggests a means ends framework That's what you've seen earlier today in which the means of production are transformed over time Into consumable output. Okay, so that stark difference between the two theories Now with apologies to many of you who have had a course in basic macro and how many would that be? okay So lots of apologies here. We're going to take a brief review of The Keynesian circular flow framework, but you're going to see it It's going to look a little different than what you've seen in the textbooks Circular flow framework and so we have business organizations, which is just a a facility To bring workers and managers together Downstairs we got all the people we got workers and consumers and investors Okay, and it goes like this Do we have labor and other factor services? being provided in the business Organizations and that's that's the right way to say it labor and other factor services because Keynes He pretty much limited the input to labor as far as actually modeling it and He assumed that the other Inputs came along with it And then we have a reverse arrow that shows the income earned by labor and other factors Now if you look at the other side You get goods and services being produced there at the business organizations and They're bought by this these expenditures of consumer Consumption and investment so that's that's the circular flow And the thing that's more unique about my circular flow than what's in the textbook Is that they circulate? Well the things off right now I'll turn it on and you get a circular flow. Okay, you see how it works It's a little bit lethargic, but you can see why the dial is set to six, you know the Federal Reserve has the Dial set at six percent Okay, if you wanted to circulate faster just turn it over to Two percent And you get a and you get a boom in the economy and then if you start getting inflation Oh, you better flip it back or stop it and then you get a depression. Okay. That's the way it works It's a circular flow There there we go now, I'm trying to get it to go right here Now Hayek has got a whole different setup and it's all based on this stages of production so the two Graphics don't look anything alike and you wonder how you can start with one and end up getting to another The Keynesian equilibrium Condition as you have learned in school Is an income equals expenditures in other words the circulating that does on the Right half has to equal the circulating that does on the left half. Otherwise you have You have disequilibrium and Equilibrium conditions income equals expenditures For a holy private economy The income has to equal consumption expenditures plus investment expenditures We could add government spending, but I'm leaving that off In this particular PowerPoint so you have a holy private economy Y equals C plus I Okay now We put that on a graph and really all we're graphing is the left side of the graph in terms of expenditures and the right side of the Circular flow in terms of income and if the two thing has two things have to be equal in equilibrium Then you get a 45 degree line. That's what the equilibrium Is defined as all right so the economy is in Keynesian equilibrium somewhere along the 45 degree line The line itself identifying all the possible income Expenditure equilibrium points we draw the consumption equation the consumption function, which is The stable part of the economy as far as Keynes is concerned although will show later that it can Change and with consequences so there is the consumption equation it's Has a lower slope than 45 degree line And it doesn't start at the origin it suggests that even without any income People have some expenditures which clues you off right there that it's sort of a short-run thing. You must have had Some money built up before you lost all your income And and now you can still spin and then the slope is Called the marginal propensity to consume MPC you've heard about that and it means the slope of that line is Lower than one in other words. Yeah, you spend but you save to all right you spend and you save and The equation of that is c equals a plus by the a is simply the vertical intercept of the Slope is b over 1 And b over 1 is less than 1 and then we pile on to consumption investment So it has that same slope but only because it's sitting on top of Consumption so investment just Is what it is It doesn't have any Determinance that we that we can derive from the market process in fact It depends on what Keynes calls animal spirit investment depends neither on current income nor on the rate of interest it depends Only on profit expectations, which themselves are not well anchored in economic reality. Well, there's a Loose joint right there. I mean sudden, you know, that's that's kind of strange But it's that's where animal spirits come in you have fire in the belly or not and so on So consumption and investment as well as government spending are Portrait as additive Components of total spending the three components are distinguished largely in terms of their stability characteristics so you have Consumption which is seen as being stable. It doesn't move around too much investment which is being is unstable and Government spending which I'm not treating in this particular diagram as being stabilizing Okay, so it's government spending to the rescue Stabilizing an economy that otherwise would be unstable because of the unstable investment Spending okay, so here when we see the equilibrium point And and we can see it's equilibrium because there's income the horizontal distance and That vertical distance is consumption and the rest of it is Investment so y equals c plus i that gives you the the stable income at least stable until investment changes So holy private macro economy achieves an income expenditure Equilibrium when y equals c plus i note that income itself rather than prices wages or interest rate is the equilibrating variable you don't have prices changing and interest rate changing To create equilibrium is simply how many workers are working Either more or less and so on According to Keynes it is only by accident or design That the economy is actually performing at its full employment potential and I've had students ask me and very innocently Well, what's it? What else is there between accident and design? And and actually the right answer is it's it's market mechanisms at work for you and for me So in other words he rules out the possibility that there are mechanisms in the economy Changing prices changing interest rates and so on that could bring the economy into equilibrium So we assume here initially full employment conditions prevail if only by accident And it has to be by accident here because we don't have We don't have government spending in the picture so it's not by design All right Now in this diagram on the right I'm going to include The production possibilities frontier although you don't see this in the texts on on Keynesian theory, okay, and you can see by By that graph that sure enough we are in equilibrium a macro equilibrium in other words We're on the production possibilities Frontier so in capital-based macroeconomics full employment implies that the economy is Operating on its production possibilities frontier the PPF itself being defined in terms of sustainable output Levels of consumption and investment goods, okay, and I've even got a labor market that is In equilibrium I'm being real fair to Keynes at this point And showing how things work at their best even if only by accident In Keynesian macroeconomics full employment implies that the labor market clears at the going wage rate And that's the term that Keynes use the going wage rate All right The going wage rate itself having emerged during a period in which the economy was experiencing No macroeconomic problems, so you have this wage rate out there, and that's that's the one we need That's the one we want. That's the one that's a sort of a no problem economy and The Keynesians sort of keep that in mind when they're trying to fix an Economy that's got problems What should the wage rate be? So labor income that's y equals WN and the US they use the textbook use in For labor hours, I guess you call it number of labor hours and so you get the in and number I don't know how they came up with it, but The hourly wage times the number of worker hours gives you income well gives you Labor income Is fully representative of total income such that changes in labor income stand in direct proportion to changes in total income, which means that interest income and Profits other incomes. They'll they they all move up and down with labor income So as long as we sort of monitor labor income, we know generally what's happening to total income Of course, that's that's not right Because like the different components can vary one with another Okay, let's see. So there's labor income is it's that rectangle there the wage rate times the number of worker hours being expended so why sub FE that FE stands for Iron in chemistry, but it stands for a full employment here. Okay, it's a full employment income So Keynes is Keynes has got it knocked here. He's got everything in doing the right thing All right now here's my circular flow in miniature Which shows that expenditures equal income But it's it's not likely to stay that way because that investment magnitude is Not stable So what might happen here? According to Keynes a collapse of Investment activity the collapse being attributable to a waning of the animal spirits He used animal spirits three times at a page and a half That's the primary cause of Economic downturns. Well, he hasn't explained much there, you know What are these animal spirits in response to reduced investment and hence reduced employment opportunities? The economy spirals downward into a recession and possibly deep depression Well, there's the animal spirits Now that would spook anybody wouldn't it and when that happens Investment goes down Now I'm making fun of Keynes. I know but and so you can see there's excess inventories there and you can see them piling up here So something's got to give. Okay. Now what happens, of course, is the economy crashes and Goes to a much lower level of income And then here's the here are the little equations you had to memorize and and using your quizzes you have the change in investment and the change in Income that was a result of it And we could even give the equation Delta y equals one over one minus V times Delta I and we can see that Consumption changes to not not the consumption equation Shifts but you move down and so you got less consumption and now which what we see is worth pointing out is that When something happens bad Then everything goes down in investment goes down consumption goes down income goes down. Okay That's that's the way the thing works and there's see you don't have any prices or interest rate in this in this equation the simple interest spending multipliers one over one minus V which You see there in the equation it quantifies the relative rates of downward and upward spiraling and now we have the labor market in Trouble because the demand for labor shifted down to all right and yet Note that the going wage rate keeps going even after the market conditions that gave rise to it are gone you'd expect that wages would adjust to that Supply demand equilibrium and when you look at the the whole model at this point It makes you wonder why he titled the book the general theory how general is it? Now I'm going to skip over here One part just because it's Redundant at least for our purposes So I'm going to do some morphing from the circular flow to a means ends framework Starting from the Keynesian view the nature of the Keynesian style spiraling associated with recession depression and inflation Becomes more transparent when the production possibilities frontier is in play and it's me of course is putting it in play Not Keynes There it is Okay, now again, we're going to watch the waning of the animal spirits Causes investment to decrease and with it in common consumption But now what I want you to look at is the PPF diagram You know what's going to happen to the other one because you've already seen it, but let's watch the shift There's the shift in C plus I and here goes the economy So what you see that the economy falls inside the PPF Consumption and investment Move in the same direction. They both go down together. They both go up together No, there's no way you can move along the PPF and again you have You're going wage, but it's not an equilibrium anymore Now we're going to shift again get even lower Shifts down some more Like that still that going wages So the further waning Sends the economy deeper into the PFS interior movements inside the frontier and beyond Trace out a linear relationship showing how consumption varies with income and And so watch this in the PPF graph. I even showing one outside the PPF And we can draw a line there Like so it's called the Keynesian demand constraint You might wonder who named it that and it turns out it's me because No one else has drawn this diagram They didn't get it Let's see. I think I show you here a note that the investment were if the investment were to fall to zero the economy would settle into an income expenditure equilibrium with y equals C no I and That I can show you just with See, I thought I had it there Yeah, that line there that little white line That just shows I've got my Graphs lined up that when there's when it shows no investment in the one diagram it shows no investment in the other one too All right Now I want to get the equation of that line and I don't expect you to follow this. It's probably too small For you to see but we can easily see what's going on. We got C equals a plus b y and C plus i And so we've got three variables In two equations so we can massage those equations and End up just with one equation with two variables. In other words, we get rid of one Variable and that will allow us show you how Consumption and investment move with one another so I do the algebra. It's just simple algebra You can do it on your own and it gives you this at the intercept there is a over one minus b The slope is B over one minus B. So there's the equation Of the demand constraint And again, it's an equation. You'll never see in a in a principal's textbook. They just don't do that as soon as you see that Consumption investment are always moving together. You see that the PPF is really just out of play I'll skip over this and in the name of Saving time but these are the numbers that Keynes himself picked out To make the point although he didn't draw the graph and he says he says that There's always an equation of this type of relationship of this type meaning that upward sloping line and it has Tremendous significance, but no one seems to realize it All right. Well, of course the reason you have this line is because the whole economy is hamstrung and Is operating with the animal spirits? That's one of his examples Let's read this part the formula is not of course quite so simple because he is he assumed that a is zero and it's not In this illustration, but there's always a formula more or less of this kind Relating the output of consumption goods, which it is it pays to produce to the output of investment goods And that's what we've done This conclusion appears to me to be quite beyond dispute And it's only beyond dispute if you've bought into all of the assumptions that Keynes has made yet The consequences which follow from it are at the same time unfamiliar and of the greatest possible importance and Of course the importance is that if this happens to an economy and it's surely well Then we need government to the rescue To get us back to a full employment equilibrium That's the story there Okay to keep track of possible interest rates movements the loanable funds market can be brought into view and Keynes probably wouldn't appreciate this because they didn't like the loanable funds market But we'll put it in the view anyhow so there's the rate of interest versus savings and investment you saw that in the In the earlier model Upward sloping supply curve downward sloping demand curve like so Though Keynes argued that neither saving nor investment depended To any significant extent on the interest rate. He also argued that both curves as conventionally drawn Shift together leaving the interest rate unchanged So this is why interest rate was out of the picture for Keynes that he thought these two diagrams if the shifts It would shift together Right or left and so the interest rate wouldn't change Okay with loanable funds market in play and I'm jumping the cadence there with loanable funds markets in play We see that decreased investment is accompanied by a leftward shift in the demand for loanable funds Putting downward pressure on interest rates will we get that far? So here's So you can see C plus I fell because of the fall in investment and then so the demand for loanable funds Fell so it shifted to the left and at this point you might think well, okay, then you're going to get a lower interest rate But Keynes says no before that can happen The spiraling downward of income implies that the supply of loanable funds Also known as saving Shifts leftward to relieving the downward pressure on the interest rate so There goes the supply and once that happens the interest rate didn't change so Keynes says well Why are we fool with this curve because the interest rate doesn't change both curves shift together, okay now I Realized only at this point when I got to the model put together that that one single diagram In Keynes's general theory and you only had one was exactly This demonstration although you wouldn't guess it just by looking at the diagram Appearing in the general theory is the specific application of the loanable funds framework The implications according to Keynes is that loanable funds reckoning is at best superfluous and This hasn't been picked up just by the by the textbooks So here's the general theory and there's his diagram I could start by asking what all is wrong with that diagram On the horizontal axis is R which actually stands for interest. I guess rate of interest so that's interest and What do you see on the vertical diagram? That's a big sin, isn't it? I see our physicists Smiling What's on the well you can see it in the in the passages Let's see as shown on page 180 of his general theory Keynes presented the loanable funds market With the interest rate R on the horizontal axis you failed to label the horizontal the vertical axis The accompanying text indicates that saving and investment are measured there. So it's the same curve I've got except it's Backwards, okay Now what I want to do Keynes diagram can be flipped over and rotated 90 degrees to make it conform To modern renditions of the market for loanable funds and we'll get that So that's the diagram now with saving and investment and then the interest rate upstairs Also, two of those diagram two of those incomes We're just to show that income is a shift parameter. So we get rid of that Okay, now that looks more and more like my diagram. In fact, the only thing different is that he's got the He's got the upward sloping thing Sort of backwards as far as bowed out. He's got him bowed the wrong direction, but we'll forgive him so he's showing that both The supply and the demand shifted a rate that keep interest rates Unchanged and therefore he doesn't need to use this diagram You can see it over there, too Keynes also denied whoop. Let me go back. Keynes also denied that an increase in saving would have the effect of Imagine by the loanable funds there is Keynes paradox of the thrift As articulated in his general theory is to the point Every attempt he says every attempt to save more by reducing consumption. Yeah, that's the way you save more Will so affect incomes That the attempt necessarily defeats itself This is called the paradox of Thrift and now for the first time we're going to let the consumption fall Okay, Keynes thought that was rare it didn't fall much it didn't fall often, but it could fall And if it does and it falls because people decide to save more Then that that really bollocks is up the economy so now almost everything will shift here because that That constraint up there that demand constraint Has the parameters of the shift of the consumption function in it so it'll shift too So let's make it everything shift that's supposed to shift it goes like that Okay Don't expect you to fully digest this particular diagram, but you can see what will happen Okay, the right word shift in the supply of loanable funds puts downward pressure on interest rates, but Here's the Keynesian part before there is any movement along the demand for loanable funds The pressure is relieved as Reduced consumption causes income and hence saving to fall Okay, so they reduce consumption that's in the economy and depression income fell and if income fell it can't save As much anymore and so the saving shifts left to and again you get Keynes's view that the interest rate isn't affected by that kind of change I'm watching the clock here. So hence the peer the paradox of thrift try to save more and you'll instead earn less That's that's the paradox of thrift and Cain really not a paradox. It's just a result of a Absolutely hamstrung economy That isn't directed by movements in wage rates interest rates Output prices or anything of the short of the sort Okay You know, let's see. I lost something there. I'll come back To resolve Cain's paradox of thrift requires that we've replaced the Keynesian cross Which reflect the economy circular flow with a hiking triangle. Okay. I think I'm in good shape time wise because now I'm going to There is step by step show what we have to do to get from Cain's to hi-hack And I sort of reset the the whole thing where we've got Just just the outline of what Of how things are set up without any shifting at this point. Okay So the level of consumption that appears as part of the Keynesian circular flow also appears as the capital based framework and as the consumable output of a temporally sequence production activities so That's consumption in the Keynesian theory. Well, that's consumption at the end of that hiking triangle So let me put that hiking triangle in there There it is So I've jettison's C plus i plus g And put the hiking triangle in Um Cain's however assumed a fixed structure of industry Which in the current context implies a hiking triangle of fixed shape The only live issue being the triangle size which presents Which represents the level of employment and the extent of capital utilization And so I'm going to I'm going to use this diagram this whole diagram here Sticking to the Keynesian principles But showing how they work out with high all right See we've still got a ppf that you can't move along So as before We begin with the economy functioning at its full employment level The labor market is representative of each and every stage of production That make up the economy's capital structure in other words. He just had the labor market And so to show that it would look something like this Okay, it's it's not stage specific labor markets It's all the labor markets and to the extent they move and all they move together Market mechanisms in play here are still those envisions by Keynes In accordance with the paradox an increase in saving Causes the economy to spiral down to a less than full employment level. Let's watch that Okay, there's the increase in savings And there's the aftermath And you see the triangle doesn't change shapes it can't in his viewpoint And so it just ends the economy up in depression And we got less employment to boot Note that the sole effect of the structure of production comes from the initial reduction in consumption the derived demand effect works undemandaged On all the earlier stages All right, the interest rate is effectively out of play The leftward shift of savings Took the downward pressure off of interest rates and in any case the capital structures assumed to be fixed So You know, nothing's going to happen. That's good in that kind of a model Okay, I'm resetting it now Now three modifications are needed to transform the Keynesian vision into a Hayekian vision. I've still got I've got exactly enough time And I want you to pay attention to which What is it that we're revising? And see if you could think of any problems with the revisions One divide the structure of production into stages all right, well I think we can do that. There they are. We've got different stages and two Allow stage specific labor markets in which wage rates adjust to change market conditions Okay, we can do that. All right I'm about to get there Get rid of the Keynesian demand constraint and we can get rid of it because Now you've got labor markets That change relative to one another and you've got a triangle that's going to change Shapes and and not just sizes And in that case you can move along the ppf and if you can move along the ppf then then that So-called demand constraints out of play All right And there's a question about how to get rid of it. We'll try this It's gone And now what you have is a is a hayekian model the paradox of thrift becomes a gateway to growth. Okay a little bit of With wage rates and interest rates both adjusting to change market conditions the economy can move along the ppf And the structure of production can adjust to increase to an increase in saving You've seen this before so you'll see it one more time and there it is Hayek says mr. Keynes aggregates conceal the most fundamental mechanisms of change Don't want to be too judgmental here Okay, there you have it


What's the word, y'all? Oh my, I decided that I wanted to hold the mic again. It was just a different feel to the show when I had the microphone in hand. I even went back to watch the original episodes that created the ramble or the recap, whatever you wanna call it. First of its time, believe it or not, the first person to hold the microphone and talk about the NBA in existence and put it on YouTube, it was me, I did it. And I went back to watch those videos and it just had a different feel than what we've been doing this season. I'm not saying what we have been doing this season was a bad thing at all, but I do like the me talking in front of a camera and a microphone and not really think about what I'm saying and then going back and re-watching the video and realizing that I said something stupid. For example, we were in the bubble and I was talking about the Lakers because if you don't remember the Lakers and the regular season of the bubble or the pre-season, all of that, the bubble, they looked terrible. And in that video, listen, I'm a man and I can admit when I was wrong about something. And I guess I wasn't, I said I commit when I was wrong and here I am saying I wasn't wrong, but I was speculating. So I didn't say this verbatim, but I was speculating whether or not LeBron James will slow it down because in that moment, LeBron was averaging like 15 points per game dog. And what we've seen this season is that he can still have average 30, but you probably don't want your 37-year-old to average 30 because it ain't working out great. The Lakers aren't great. And I've been a guy that said plenty of times in the channel, I was gonna refrain of talking about the Lakers extensively until I got a bigger sample size, over 30 games to the season, they still are bad. But this video is not supposed to be about the Lakers, but that's what the Ramble is, ladies and gentlemen. So we had a slated game today that was super interesting and super fun. I will say that Dejante, remember I'm giving you your love right now which are 24, 12 and 13. I did not watch your game, my boy. I'm gonna make it my sole purpose tomorrow morning to watch this game that was a 20-point blowout because I feel like Dejante Murray is one of those players that I absolutely would love if I watched more of him. When I do watch him, I do enjoy watching him play, but I just, the Spurs have this point in my mind where it's like a mental block and it goes from the years of Tim Duncan where I just wasn't watching him because in my mind they were boring and in reality they were just good. And now, I don't know, would you call them boring? I haven't even watched out of the 30 games I can count on a single hand how many times I've tuned into the Spurs games. And you know what? That's my fault. That's not their fault. That's my fault. So Dejante, I promise you, tomorrow morning I will be tweeting about you because I will watch this game. But I wanna see other ones. And I hit my boy Bucks up, shout out to Bucks. He's my thumbnail designer. He's been doing it for what seems like two or three years now and he is so flexible. Typically I'll just tell him the title of my video and he'll come up in his brain and come up with something great. And I told him, let me read you what I told him that the title of this video was and I don't know if I'm sticking to it. Rambling about the NBA and making people upset. Because I want to stir the pot on many things. I want to stir the pot on many things. Let's talk about the Kings at the top of the show. Let's see who that gets us. They went to go to say Warriors today. They go and say Warriors are the best team at basketball. I guess you can say that. I'm not looking at the standings but I know it's them and the sons at the top. And you know, they're missing some players like everybody in the world is. So they had Jonathan Camingo start. Shout out to Jonathan Camingo. He has like a 20 plus game, 27 point game from that mistake in last game. And then I guess it was Steve Kerr. He was asked about it. He was, and Steve Kerr basically told him if we were a rebuilding team or a bad team you can put that up every single night where we're trying to win and we're trying to develop you. So today he only plays six minutes. He put up 27 the game before and got six minutes to game after. Development. A little bit different on the warrior side. Let's see how that works out for them, man. Because obviously he can hoop, but they're playing so well. Like Iggy has such a game. He threw the behind the back pass and he's playing the defense, yada, yada, yada. And when you have him playing well, you have OP playing well and you got Gary Payton a second who don't want to call. He doesn't want to be called the mitten which is a missed opportunity if you ask me. But I understand the glove feels more like a real nickname with some value and like it's not necessarily soft but when I think about a mitten I'm thinking about it. Like you could say a glove, a baseball glove, yada, yada, yada. They got some thick leather on that. That was Gary Payton. And a mitten I kind of think of like, oh, you know what I'm saying? Oh, I don't even have fingers.  Okay, so the last couple of days the Kings are another team that has hit heavily with health estate, the protocol and some injuries here and there. And because of that D'Earn Fox has been out with an injury. And I am here to just say they need to build around Tyrese Halliburton because over these last couple of games what I've seen in Tyrese is a guy that for the first year and so of his career he's been trying to find the balance of being able to score or when to score and when to pass.  And by nature he is a past first guy but with D'Earn Fox not being in the lineup and him being the focal point of the offense he's been able to find a balance of when to score and when not to score and when to pass. And he doesn't really have that opportunity with D'Earn Fox. Now I think, I don't know who made the tweet and there's somebody I follow and I apologize. I mean it was a mean tweet or a joke tweet but every joke has some form of trueness in it, right? And they put a picture of D'Earn Fox and D'Earn Fox and Tyrese Halliburton and then a picture of Maté Alice and Steph Curry saying it was time to make that decision where you might have to break up the backcourt for the better of your organization. Like D'Earn is not necessarily having a good individual season but I still believe you can trade D'Earn Fox and get a lot of value out of him because what he's 24, 25 years old and I think most people realize that D'Earn Fox is still a really, really good basketball player and I would still put money on the fact that he will be an All-Star eventually someday but the backcourt last year they struggled together. See the Ramble was never supposed to be like looking up stats and stuff but I wanna make sure that I'm still thinking about things the right way. So yeah, last year when they were together on the court they had a net rating of minus 4.7. Again, we're not an advanced stat channel but I think it says a little bit something. And this year's at a minus 4.7 and sometimes you see this in NBA history all the time where two players just don't fit together because I want Harry's hella bird and run in my offense because what we've seen over this very small sample size that we're determining the rest of our franchise on is that he, with the ball in his hands he is a great playmaker that can find the buddy heilds of the world, the Harrison Barnes and I guess in this case, Chamezi Metzl was a God. And when you're doing something like that, when Harry's is the primary ball handler and D'Earn Fox is doing whatever he's doing, he's not much of a threat. If I am the opposing coach with Harry's hella bird at the top of the key doing what he does to try to create offense for his team, I'm not guarding D'Earn Fox. I'm preventing him from cutting to the rim but other than that, if he get an open look in the corner we doing one of these on him, shoot the ball my boy. So I would love, here's the two moves that I want the Sacramento Kings are doing. I'm not telling them to do that right now. I'm not telling them at the trade deadline, trade D'Earn Fox. But I'm saying that they're gonna have to make that decision. This is what I want them to do. Make the decision on D'Earn Fox, what the right pieces is or who the player is. And I know there are some people that already wanna see the 76ers, Kings win. And I think that might be the best because the Kings need defense and the guy that name I said yesterday that I wasn't gonna say anymore until he's actually traded. He can bring that to you, whatever, figure out what that is. And second, maybe Rashawn Holmes is his dude actually. Not that I'm thinking about it. Terry's Halliburton is a guy that loves to throw the lob. Chamezi Metru of the last couple of games eating off the lobs. And maybe Rashawn Holmes is that dude when he's coming back from his injuries. But he needs a like real life, big old lob threat, continue to put the shooters around him or there it is buddy, whereas it is a TD or Harrison or whoever it may be and let him go to work, man. You wanna see the playoffs? That is the key. I'm giving you the keys to the car right there. But D'Earn, I do wanna make it very, very clear, very apparent. I am still a big time fan of D'Earn and Fox. All right, I just wanna quickly transition to OKC versus Grizzlies because the last time OKC played against the Grizzlies, they lost by 73. And here they are with a win. And I guess we gotta talk about this Jamerran stuff because apparently I'm looking on my Twitter account right now Jamerran heard by fans telling him to sit back out as Grizzlies lose. I don't like the wording of that article by fans telling him to sit back out. Sit back out. It just don't feel, anyway, I guess there were some fans core side and the process of the Memphis Grizzlies losing this game, there's some people core side telling Jha, we better without you. And if you look at the replies of his tweets, like he said he was going zero to dark 30, he not going on social media for a while, which kind of sucks because I think Jamerran's one of the better Twitter followers and Instagram followers and the NBA. If you look at the replies, 99% of fans are going to agree with me when I say, Jamerran is Memphis. He is the star of Memphis and yada, yada, yada. That one person or two people sitting core side does not represent the entire organization for sure. But what I will say on Jamerran's behalf is that it's hard to drain out that one person to say something negative about you. Even if Jamerran has a million fans in Memphis that are saying we love you here and we love, we want to keep you here. We want you to sign that max extension when you get eligible for it. It's hard not to hear that one fan. It just is. I know a lot of people say, ah, you get paid millions of dollars. You got to have thick of skin, but it's easier said than done. That's all I'm really saying. But, shake your hand, Alexander. The clutch gene is a real thing. I've had this conversation with people and there is a percentage of sports fans in general that will tell you the clutch gene is not really a real thing. I am a firm believer that the clutch gene is very real and his last three games are proof of it. Shay hits a crazy half court shot when he was trying to draw a foul. Devonte Graham ended all of that, by the way. Shout out to Vonte. Game after that, hit Nicholas Batum and a nasty step back, waited one second to make sure that the time ran out, hits the three and in this one, I don't remember the exact play by play, but I think I made a tweet about it. He got an assist. These are the last couple seconds of the game. He got an assist after drawing a double team. I think it was down to Josh Giddy who will talk about coach Mark D end up drawing a good baseline out of bounds player, sideline out of bounds play that I've definitely seen some high school teams run. Got an open layup for Shay. He got a steal, then iced it with two free throws. Now it wasn't the step back game when they're like Nicholas Batum's game, but like those are super clutch plays from one of the youngest up and coming stars in the NBA and I will not forget about it because Bleacherport has not apologized a month ago. Less than a month ago, they were ranking the 24 players under 24 and Taylor Horton Tucker was above Shay. This team lost by 73 to this exact organization two weeks ago and Shay comes in, he's like, I'm gonna win us this game and he did. Not okay, it wasn't all Shay because Lou Dorot still has his three point streak in this game. I mean, he was 27% from three, but hey, he hit his three and he ended up having a big time block down the stretch. We're gonna count that. And Josh Giddy, career high, at least I think he tied a career high, ended up with 11 assists and that's coming off a game two nights ago. We had 18 rebounds. Josh Giddy, there's a meme before the NBA draft and they were doing like a scouting report on Josh Giddy and it was like weaknesses, shooting, finishing, defense and somebody quoted and it was like, so basketball, his weakness is basketball, but what we see in his weakness is not basketball, that is his strength. He can play make, he can rebound, he can hit shots, he can do a lot of different things. So shout out to Josh Giddy, man. They called him, oh man, why did I see his nickname was? It's not super relevant. Go win for OKC. The Bulls got revenge on the Houston Rockets and I needed this win for my blood and soul because the last time we played against them, we jumpstarted this team to a game one streak. So I'm happy that we were able to win this one. DeMarco Rosen being on my favorite team is a blessing. And you know what? Like I mentioned earlier, I am a guy that can admit when they're wrong. I talk about sports for a living, I'm gonna be wrong tons of tons of times. Yes, before the season started, when we were raking small forwards in the league, I did have DeMarco Rosen kind of low, but here's my excuse. Yes, I'm saying again, I was wrong, but here's my excuse. Bro was not playing an MVP caliber last season. He was not playing an all NBA caliber last season. I did not see this coming. If you saw that DeMarco Rosen was gonna jumpstart into an all NBA players slash MVP candidate. Now, when I say MVP candidate, everybody knows the Core 4 right now. It is Giannis, it is Steph, it is KD, and it is Jokic, that's Core 4. But if you're looking at number five, DeMarco Rosen really has a case there. You didn't see that coming. If you did, you should have put money on him. My God, because you'd be a millionaire right now because the odds were not in his favor. So I did have him relatively low. And I was wrong. And I'm happy I was wrong because now the bulls are okay. Legitimately, carrying an entire offense. Now, I would like for other people to wake up a little bit more so he doesn't have to do all of this. But again, we are still missing Zach Levine who's at home watching games and everything. Shout out to DeMarco Rosen. I will not disrespect you ever again in your career. Cause again, yeah, last year he was good. I'm not saying he was scrubbed last year. He made my list, but I think it was gonna be this good. And also, if you go back and watch those videos, I have a tendency of ranking my favorite player, my favorite team's players lower because I still don't know if I'm higher on my favorite favorite players than I should be because they're my favorite players. And I think I've talked about that before. I think Patrick Williams could be the next coming of whatever. And you may not think that way. And maybe it's just because he's on my favorite team. The Boston Celtics continue to let me down. And I mean, I guess it's not really letting me down because I'm not rooting for them, but like they were up with like three minutes to go. And I was typically we're in a party watching these games together. And I remember telling Mike like, the 76ers are gonna win this game one way or another. Cause I was not confident in the fact that the Boston Celtics can close out this game. Now I will say Jason Tatum and Jaylen Brown can make a ton of clutch shots, isolation shots, yada yada.  Even the games that they pull out where JT does hit a big shot or JB does hit a big shot. I walk away from that saying, ah, good win. But it didn't have to be that difficult. When I watch Jaylen and Jason play basketball, they make things look so difficult. When it's going in, it's like, man, them dudes are beasts because they make the difficult shots. But when it's not, it's hard to watch. And today specifically talking about the last three minutes was extremely, extremely hard to watch. And what I would hate for the Boston Celtics organization to do, whether it be this season or next season is to make the ultimate decision. And you know what I'm talking about, whether or not you want to keep or get rid of one of these core guys. I do not think the solution is to trade Jaylen or trade Jason or pick between the two. What the team needs is a guy that can facilitate. Simple.  But these dudes have not played with a person that can set them up and have a Florida offense ever. And they just need that down the stretch. Jaylen Brown turnover, Jason Tatum turnover. They don't have the guy to set them up and they haven't had that at all in their careers. And I would hate for them to split up these core great young players without at least trying to get them a point guard. Now, if they get them a Ricky Rubio type guy they can really facilitate and get everything going and they steal a trash, make your decision. But don't make it yet is what I'm saying. Jaylen and Jason can work together. It's players three through 15 that can't. Now, again, they are missing Robert Williams and Al Horford in today where they had Joel and B beating up on freedom. But still, the idea is the same for me whether or not Al is there or Big Rob, Time Lord is there. They need somebody to get everybody involved and they don't have that, all right? But Joel, when Joel is playing 40 plus minutes it's a sight to be seen, man. I think he's averaging 42 points per game when he's playing over 40 minutes. And they were talking about that on the Celsius broadcast how per 36 Joel and B is like top five all time, per 36 with some type of filters because I bet per 36 of some dude that scored one basket in his NBA career, boom. His per 36 is 144 or whatever the math works out to be.  This team won a game where they had one point and they contributed from the bench. One singular point. Tobias Harris was very, very clutch here. I love when he is a third option. Seth Curry is a Kenny for an All-Star. We'll talk about him eventually one day. He's a Kenny for an All-Star.  And when I am super impressed with Joel and B it's his ability or his uptick in like his playmaking ability. And I'm not saying that this wasn't always there. I mean, now you have extra assist to dish out because Ben Simmons is not there. This is a team playing without a point guard right now. Like real life playing without a point guard. And they ran the ball through Joel and B and seemed like every single possession. And he did an amazing job when the double team started to come find his shooters. Danny Green, big shot in the corner and Seth Curry, 74% from the field, three from three from three. Joel and B was amazing today. One of his best games of his career was tonight. And that's a good comeback because again, the last time they played against each other he's stunk. And maybe that is just because Al Horford was there. I will say this though, even before Ennis freedom changed his name and he was talking all on socials and going on TV shows, I will say this. And I think I'm on record saying this years ago. I like watching Ennis Cantor or Ennis Freedom get killed in a game. It's so hilarious to me because I guess that's my cue after this statement. It's so hilarious to me because he doesn't look like he's giving effort. I'm not saying that he's not. I'm not saying Ennis, if you're watching this, I'm not saying you're not giving effort. But when I watched Joel put up 41 points today it feels like a lot of them were like not contested shots. Some of them he was legitimately walking to the basket and it was like, here you go, here's a layup. But it's fun. I feel like 90% of centers can see freedom on the other team when he's in the game and like, all right, let's go get some buckets. And they do. The only bad thing about these type of formatted videos is they tend to go way longer than I wanted them to. Like I didn't talk at all about Charlotte, who can't score in the first quarter. But you know, once things got together, after that first quarter they played a lot better and Lamello ended up with 20. Ted Rosier had a good bounce back game because I don't even know if he got on a board last game, I might be exaggerating a little bit, but last game was a huge, huge stinker. I took the over on Rudy Gobert tonight. This is not a plug for prize picks, but if you want to download it, go ahead and do that. I took the over because they were going to get the Hornets and just the night before they let Javel McGee drop 19. So I'm like, hey, if Javel McGee can drop 19, I know Rudy Gobert can give me 20 and he gave me a 20-20 piece. So shout out to him. Don't expect these to happen every night, by the way. I actually have to have something to say for me to do like a Rambo, even though I probably didn't say anything.


But we're not going to be like mothers that sit there with all of our children being lined up and shot.  They're doing that to their people. What were they doing in an hour? That's right. Now, as it is, they'll say, well, you ought to have done so-and-so, as I look back, you ought to call the meeting of the United Nations, as I had them debate for a while longer.  So either way you go, you got it. But the point is this. We haven't killed anybody. And they haven't killed a single civilian up to now.  But they're not an American because we surrounded them, we'll put our people around them, we've put cut off the zone, and we have not lost an American life as of yet. Now, the snipers picked off six of our Marines from top of the building. We weren't killing Dominicans. We were there protecting Americans and 36 other countries.  And I told McNamara, after the orders issued, I said, now, let's don't get some wild bully or some captain that'll start shooting up the street when they invade on him. Let's get the best man we've got in the United States Army, send him, put him in charge, tell him to use a cool head, and his job is not to kill anybody, but to keep any of our people being killed. And that's it.


Welcome to the lecture on Analysis of Algorithm, Time and Space. At the end of this session, students will be able to list and determine the criteria for analysis of an algorithm, analyze a simple algorithm using step count method. We will also be discussing how to write an algorithm, what means analyzing algorithm, the criteria for algorithm analysis, time analysis, space analysis. Now, when we say how to write an algorithm, means consider the given example for algorithm swap AB, here if you notice this is a simple algorithm with three statements where the intention is to swap the numbers A and B and it is being done in a very simple way, here the use of curly brackets has been done to write the three statement, however the alternative way suggests use of begin and end with the same statements written in this format. Now the third format also for algorithm swap says the same thing, however here begin and end is replaced by curly bracket and here the assignment operator is replaced by arrow operator. If you notice the same algorithm is being written in three different ways, so what we want to convey here is there is no specific syntax for writing the algorithm, the algorithm has to be written in a way that is been understood by the programmer and the person who is going to use it, so as long as you use a conventions which are understood by both of them the algorithm is fine. Now we move to the analysis of algorithm, algorithms are nothing but the procedures for solving problem either manually or using computer, the criteria for algorithm analysis basically includes time, time means time function, how much time is the algorithm going to take, next is space, space means how much memory space is the algorithm going to occupy, third criteria is the network, if the algorithm is a part of network consider like uber, ola app, swiggy where these are the algorithms that are working on the internet and there is a to and flow of the data packet. Now this also needs to be considered, the fourth important point is the power consumption, when you are running specific apps for example google app, for going from one destination to other most of the time it is been observed that as there is lot of multimedia data involved in google map the power consumption is more, so much power is being consumed and finally the CPU registered, this is most of the time being ignored, however for our discussion the major criteria is time and space, so we are going to consider the time function and the space function, moving ahead when we see how much time will it take means it is not the watch time, it is actually the time required for the executing of the algorithm and how do we do this, we do this by considering the same example of algorithm swap. Now when we say we are interested in finding out the time, for this algorithm means here it is not the watch time, it is the number of steps, number of unit of time, now consider this statement if we see this statement requires one unit of time that is temp A, A is equal to B requires one unit of time, B is equal to temp again requires one unit of time therefore this entire algorithm swap requires three units of time that is function of f of n is equal to three units of time. Now we will consider the space analysis of the same algorithm, if we see here there are one variable that is A, the second variable that is B and here we have the third variable that is temp, each of this requires one unit of space and therefore we say that the space s of n is equal to three, when we want to convert it and what is this three, this three is nothing but a constant that is o of one, so the time complexity of this loop is o of one, also the space complexity is o of one that is constant. Now moving ahead to the next example, now the algorithm sum here you have the algorithm sum with A and n, now perform the addition of this array of n numbers, so here we have a loop, now when we say we want to analyze the working of this algorithm means that we have to understand how much function of time that is unit of time are required for executing this loop, now consider this statement this will require one unit of time, this statement will require n plus one, now how is this n plus one, this is because this statement will be executed for one time, i is less than one will be executed for n plus one time, means if the value is five it will check for five less than five also plus one, so this particular loop will be executed for n plus one time, now however whatever is inside this loop will be executed n number of times, so whatever is inside this loop will be executed n number of time, now it is important for us to understand that this algorithm after totaling we get f of n is equal to 2n by adding this execution of every step we will get 2n plus 2 that is p of n is equal to n, n is here nothing but linear that is o of n, now consider the third example for finding sum of two matrices here the algorithm add is given add a b n, now this algorithm has one for loop with i second for loop with j, now in order to understand and compute the time complexity of a nested loop we will execute this one after the other, when as in the previous example we have seen that the for statement gets executed for n plus one time and whatever is inside the for loop will be executed n times, so for that sake this statement will be executed n time, this second statement also will be executed n time, now for the second loop that is for j is equal to 0, j less than n j plus plus, this statement will be executed for n plus one time a senior, now whatever is inside this loop will be executed n time, so this n is of the first for loop this n is of the j loop, on performing the multiplication we get this n square that is 2n square plus 2n plus 2 that is p of n is equal to n square that is quadratic, now here we will understand and see the space complexity for the same program, as we can see here the variables that have been used here are a, b and c, the space is here required for n that is n square, b, n square and c, n square and for n it is x1, i it is 1 and for j it is 1, on adding this all variables we get s of n is equal to 3n square plus 3, so reducing it we have s of n is equal to n square, so we can from these previous examples we can trace that here when we have nested for loops the execution frequency goes on increasing, so for finding the sum of two matrices the time complexity t of n is equal to n square that is also the space complexity s of n is equal to n square, now pause the video for some time and solve the following code for finding the time complexity, the answer is n cube, as we have seen that nesting of loop causes the for loop to be executed n plus one time, here there are three loops and then multiplying by n into n into n gives you it as 3n cube, therefore on reducing that we have t of n is equal to n cube, these are the references, thank you.