My name is Amy Carroll and I'm a science enthusiast. My name is Vicky Lazar and I'm a science enthusiast. We're members of the catalyst. That's a science entertainment collective based in Switzerland. So before we jump into our talk, we want to find out who's in the room. So if you have a PhD master's in any kind of discipline, raise your hand. Okay. And if you've done work with applied improv and scientists or doctors or researchers, raise your hand. Those of you who would like to work with researchers, you're curious. Excellent. Okay, good. So we're going to talk to you today about why researchers are stressed out, why that's a problem, and how improv and you can be part of the solution. So who here has ever had a round of antibiotics? Don't tell us why. Yeah, no details. We don't want to know why. But some of you might know that Alexander Fleming discovered penicillin. You may not know how he went about that. So Fleming was notoriously messy. He had a really, really messy office and in August 1928, he went on a family vacation for a month and he left his messy office behind. And when he got back to his office on September 3rd, 1928, he found that one of his bacteria cultures had gotten contaminated with this fungus and everything inside of it had died. And that fungus was from the genus penicillin. He used to call it mold juice. Like branding issues, anyone? But he moved beyond that and that's the penicillin that we all know and appreciate today. But can you imagine if Fleming had been too stressed or too overworked to take that month-long vacation, we may still be without penicillin today.  But actually that's happening right now. We have a mental health crisis in academia today. In fact, the European Council of PhD candidates and junior researchers recently held a webinar that was called How to Stay Sane in Academia. So let's throw some numbers at you. 6% of the general population report feeling seriously stressed, depressed, anxious. That number shoots up to 41% for researchers and 50% if you're a minority. So why is it so hard to be a grad student? Maybe our entire audience could share with us. Shout out some reasons why you found it difficult or you're finding it difficult now. Expectations. Competition. Yes. Isolation. Lack of control. Criticism. Volume of work. Impostor syndrome. Funding. Time. So here's the thing. Researchers are living in a world that no longer exists. Back in the good old days, it used to be that you go into academia and you were pretty much guaranteed a position as a tenured professor. Today, only 10% of people who get a PhD go on to get a tenured professorship. The number of grad students has increased wildly. The number of positions has more or less stayed the same. So that concept of publish or perish, they take it literally. They feel like if they fail in academia, they fail in life. But as this room knows, there's loads of career options out there if you have a PhD. There's lots of things for you to do. But no one is talking about that to the people who are in the process of getting their PhDs. So here's the thing. Academic institutions have caught on. They're creating soft skills training. They're creating career coaching opportunities. They're doing some counseling. But they're big heavy machines and they take time to get started. So while these big heavy machines are getting their act together, we think it's time for a grassroots approach. And we believe improv can be part of the solution. And sequence. We want to give you some background. The catalyst, that's a science entertainment collective based in Switzerland. So in 2006, a woman by the name of Adrienne LeBouf, she was in New York here studying at Rockefeller University. And she's like, man, this PhD life, this is tough. So she decided to create improv drop-ins as a way to manage her stress and bring in more joy in her life. Fast forward, 2012 she moved to Switzerland and she creates the catalyst. A science entertainment collective based in Switzerland. That's right. And the catalyst, what we do at the catalyst is we offer, it's three goals we have. One, to create a community for scientists. Two, to help them communicate their research. And three, to, what is the third one? To create new media for the public about science. Exactly. And so we are science enthusiasts. We will be sharing some quotes from some of our scientists throughout the talk to share their perspectives. So how we do this? Well, we all know drop-in is a gateway drug. Want some drop-in? Want some drop-in. Do you want to take some drop-in? Just a little. Do you want to try it? Yeah. Because we know that people who play together stay together. And then the people get excited to be working together and they create all sorts of other grassroots initiatives. Science podcasts. Science theater. Science improv shows and museums. Science film hackathons. Science podcasts. Did we say that one? Yeah. Well, podcasts are best. Right. So lots of different initiatives. And one of our researchers, Sophia, who studies the biology of sleep, she said, it's so amazing to see serious scientists get out of their shell, express all their cooped up boundless imagination and creativity and be super silly. Now, we've looked at the benefits and we've categorized it into three sections. There's the benefit to mental health, to the research, and to the science communication. So let's talk about mental health. You all have your experiences. And we've actually have a statistic that 15% of researchers feel worthless, trapped and stuck. And by its nature, research is full of failure. Experiments fail. Articles get rejected. Funding gets denied. So that idea of publish or perish is compounded with each failure. Remember, they're all keeping their eye on that one in ten. But with improv, we create a safe space where failure can be de-dramatized. Mistakes can sometimes lead to innovation. The researchers learn resilience and improv, and they can take that with them into their work. Here's what Christian had to say. Now, he used to be a PhD at the famous CERN. Improv teaches us to accept failures, creating this mindset to explore and to play. And John, who's a postdoc studying virus biology, describes it like this. Improv is incredibly therapeutic, given the high stress environment of scientific research. It's a way to step out of the real world for a bit and to play around in whatever other world your mind can conjure up. And as we know, improv creates community. It gives researchers much-needed support. One of my favorite quotes is, I love how improv gets me out of my head. I consider it a key part of my weak and self-care program. The drop-ins are a weekly chance to be with people who love and care about each other. Enough in the mushi stuff. What can this do for science research? Okay, so scientists are trained in critical thinking. It's really important that science has solid foundations and everyone can trust it. But sometimes there's a bit too much emphasis on the proving the hypothesis, this narrowing, the getting, getting, getting down to the point. And not enough time spent in that fun first phase of the scientific method, the exploration, the discovery, coming up with the hypotheses in the first place. So what does improv do? It offers the ability for more mental flexibility, for divergent thinking and for collaboration. One of our scientists said this, I get out of roots much faster. Who's surprised? Improv enhances everyone's ability to think with greater creativity and innovation. And for scientists, it teaches them to collaborate in a very competitive environment. Enrico, who's a PhD in engineering and material science, said this, I've become much more creative in and outside of research, taking the time, patience and enthusiasm, not to turn down any ideas right away, whether they're mine or someone else's. And then I see where that leads. I try to do this in everything, research or not. So here we are at the Alan Alda Center for Communicating Science. What happens when you've created your amazing creative research? Yeah, communicate it. So what our scientists have said, that they're able to speak more effectively, more confident, more calm, they're able to get their message across in a crisp manner. They listen better and then when things don't go right, they can adjust more easily. And not only is improv good for scientists trying to communicate their research, it's also good for audiences listening to science communication. One of my favorite anecdotes is from Patrick, who's a postdoc in chemistry. He said, I had to present my research after someone else had already sucked the last little bit of energy out of the room. Of course, not talking about any Izzy or Ruth or anyone else who spoke before it. So, back to Patrick. I decided to first pass around the clap. The principal investigators loved it and didn't want to stop. Again, it was worth giving my presentation. So here's our call to action. I think you'd all agree with us that improv supports researchers in their mental health in their research and in their communication. This translates directly into creating a more positive impact in the world we live in today and the world in our future. So we want to ask all of you to offer your services, develop communities for researchers where you live, help researchers develop their skills, encourage them to take ownership and model for them how to lead their communities mindfully. Our invitation, create inclusive improv communities in universities and research institutes around the world. Let's ensure the Flemmings of tomorrow can realize their full potential and communicate and contribute to the world today and in the future. Inside and outside of academia. We're Amy and Vicki, signing off for the catalyst. Science Entertainment Collective in Switzerland. Thank you.


Good afternoon. I'm Mark Thornton. I work here at the Mises Institute and it's a pleasure to address you all this afternoon. Our topic today is the minimum wage, which seems to be a big step down from some of the giant topics that we've been discussing here the first two, two and a half days. You know, competition by itself is a huge topic. But the minimum wage comes at the end or towards the end of the second day as an application of what you've learned so far. You know, subjectivism, marginalism, money in banking, the business cycle, entrepreneurship, competition and within that there was a very technical lecture on prices, price theory, price determination, what are prices and how do they come about?  You know, that it was just kind of something that came from external factors or maybe some devious person inside the marketplace. And prices really applied to labor, that's what wages are. It's the compensation to labor. And so the application here, the minimum wage is an application of government intervention into the price system. So we could have picked any price control and showed you all of the results and basically any kind of price control including minimum wage laws are going to upset the marketplace. It's going to cause disturbances, it's going to cause disruptions and it's going to distort the market for labor and in this case the market for unskilled or low skilled workers. Now the great thing about this application is it's all tangled up in a great ethical debate. The minimum wage law really only applies to about one percent of the workforce in the United States. So if you looked at that one percent, the amount of discussion by politicians, the words printed online and in newspapers and on TV news and elsewhere, the minimum wage gets a whole lot of coverage. It's a great ethical debate in the American populace and yet the statistical impact of the minimum wage is very small. If we looked at the overall workforce and the overall unemployment rate and we increased or decreased the minimum wage, it would have a very, very small, almost negligible impact. So we not only want to understand what the minimum wage does but we also want to sort of weave through this great ethical debate and the debate that's actually developed within the economics profession. At one time everybody in the economics profession was more or less agreed that the minimum wage law caused unemployment and it hurt the people that it was designed to help. And we'll also learn to understand why this is now more of a debate. As a matter of fact, there was a letter to, I think it was in the New York Times and the Washington Post and the Wall Street Journal many years ago where 75 leading U.S. economists or economists in the United States, they weren't all American citizens, but they supported an increase in the minimum wage and that included people who had won the Nobel Prize in economics, people who were part of the President's Council of Economic Advisors, leading government officials and so forth. So what is this minimum wage law? Well, you probably all have a pretty good idea. It's a law that establishes a minimum wage which employers must pay that wage per hour or more than that per hour or face, fines and other penalties. There's a federal minimum wage law which currently is $7.25 per hour mandatory minimum wage. There's state level minimum wage laws and there's local minimum wage laws. Here in Alabama we don't have a minimum wage law. So employers and employees are forced to use the federal minimum wage as the barrier. This is a quote-unquote progressive policy that was developed more than 100 years ago by the progressives in the progressive movement. It was a leading intellectual, academic, political movement that was very influential in the United States. You probably have learned a little bit about the progressive era, the early 1900s in the United States, all of the constitutional amendments that were passed during that time period, women's right to vote, for example, we got legislation for a central bank for an income tax, a constitutional amendment, we had a constitutional amendment to ban, prohibit the sale of alcohol within the United States. So plenty of crazy things or radical things or revolutionary things for good or bad. Now this progressive policy was designed to reduce employment for certain groups. It was designed to create an incentive for employers to discriminate in the workforce against women, children, and minorities. So the idea, the construction of the minimum wage law was not anything like we think today. And as a matter of fact, just like any other government law or government policy, it usually is called something that everybody can agree on, but its effect is usually designed to help this half of the room and to hurt this half of the room. Can you think of any policy that is named properly for its effect? Can you think of any policy that doesn't make some people worse off, making other people better off? That's sort of a general result of government intervention within the Austrian framework. It was designed to help high skilled union workers, high skilled factory workers, particularly white men, get all of the jobs and to get children out of the workforce for sure, but get women out of the workforce and get minorities out of the higher paying jobs, the factory jobs, and to relegate all of these people to homes and to secondary type jobs. So in that case, I mean people were asking me, I've given this lecture many times before, and people were asking me, well are you going to come out in favor of the minimum wage this time? And I do try to change this up. So if you go back and listen to my lectures from other years, they're going to be at least somewhat different from year to year. And so this year, my statement is that the minimum wage does work. It works as it was intended 100 years ago. Now this is obviously not a libertarian policy. This is obviously not the free market at work. Okay, in the free market, in the libertarian world, the employer and the employee should be willing or should be able to negotiate any contract they want as long as they can come to an agreement on it. This sets a bar. This sets a block to the prevention of certain types of labor contracts. Now in the US debate, I'll just go over a few points and then try to summarize. One side says that the minimum wage law is necessary and critical. This is not necessarily the progressives that I'm talking about here. It's the modern progressives or modern mainstream media or modern politicians, that sort of thing, that we have to have a minimum wage that it's absolutely necessary and critical and we need to raise it. We need to raise it to a living wage and things of that nature. The other side says the minimum wage causes unemployment. Boom, end of story. Now the actual confusion between these two points of view and reality is that typically the minimum wage involves, if it involves any analysis whatsoever, it's only a short-term analysis, which is not really relevant to a long-run policy. At the end of this lecture, we're going to circle back and look at the long-term effects of the minimum wage. In other words, after a teenager has or has not had a job, after they have or have not gone to college, what happens to that individual over the long haul? I'm interested in that. We all should be interested in that. And it's a wage-rate only analysis. And by gosh, wages are an important consideration to any job, but it's not the only consideration. And Austrians look at every angle in any kind of market, any kind of contract. But price is obviously important, but it's not the only thing. It's not a single aspect of your life or your career, even though it is important. A third part of this debate is that it's carried on largely on a statistical basis, even though there are so many confounding factors in the real world. In other words, this debate is entirely missing the wisdom of Frederick Bastia, Henry Haslett, and so many others. So it's only the Austrian approach that provides a correct method for understanding this issue and it's theoretical. And it's also going to be consistent with the facts, no matter how confusing, convoluted, and unreported they may be. Now, the positions on the minimum wage law and its debate currently, I break it down into three different categories. First is the hysterical sort of category. They're not actually hysterical most of the time, but it's a good reference point to remember this. This side of the debate says that the minimum wage is absolutely necessary, that it's critical, that people's lives depend upon it, that people are going to starve and die, and so on and so forth. It's necessary for the very survival of people. Of course, there's equity in fairness considerations, and then, inevitably, in recent years, you'll hear statements, well, the rich are getting richer, but the poor are getting poorer. I'm not going to talk about that now because I have another lecture on Friday morning at 11 o'clock that you won't want to miss, where I completely debunked that whole idea. The second position is empirical. This is the position of most economists now, since the Card and Krueger publication in 1996, where they raised empirical questions that showed that an increase in the minimum wage can increase the number of jobs. A whole lot of economists who are mostly progressive-minded latched on to that idea, latched on to that one empirical study which we'll talk about. And then there's the theoretical side, which is the Austrian side, which is based on economic theory. Now, we generally hold with most of the empirical economists that say that the minimum wage laws do cause unemployment, but we also look at the bigger picture. And the big picture reality is that you can't raise wages and benefits for everybody in any kind of economy. You can't just legislate higher standards of living really in any shape or form except for redistributing money from the unfavored group to the favored group. So the debate is characterized by two separate points of view other than this Austrian view that I'm going to explain today. On the one hand, the left hand, I'm going to quote a prominent economist, there's just no evidence that raising the minimum wage costs jobs, at least when the starting point is as low as it is in modern America. This apparent defiance of the law of supply and demand occurs because, quote, the market for labor isn't like the market for, say, wheat, because workers are people. So that's the left hand of the one hand. The other right hand is the more normal approach. Quote, any econ 101 students can tell you the answer. The higher wage reduces the quantity of labor demanded and hence leads to unemployment. Clearly these advocates of the minimum wage law very much want to believe that the price of labor unlike the price of gasoline or Manhattan apartments can be set based on considerations of justice not supply and demand without unpleasant side effects. Now, the left hand view is represented by a very prominent economist. There he is. That's Paul Krugman, Nobel Prize winner, lead economic columnist for the New York Times and good buddy of Bob Murphy. They actually made an agreement long ago that they would motivate and elevate each other's careers.  The right hand view is also Paul Krugman. Surprise. Paul gets to say a lot and he says a lot of things. Some of them actually pretty good but mostly bad. So let's get it down to brass tax here. Economic analysis 101. This is a graph where we have the wage rate for the market of unskilled labor on the vertical axis and the quantity of labor in the market along the horizontal axis. We have supply and demand curves which you've all looked at. You've all been exposed to Jeffrey Herbender's lecture and other lectures and this will continue throughout the week about the laws of supply and demand. And with those particular supply and demand curves there's an equilibrium wage at W0 resulting in a equilibrium level of employment L0 along the horizontal axis. Now if the government comes in and intervenes in this market with a minimum wage law you see that jumping from the equilibrium wage to the minimum wage of W1 and this means that the supply of labor actually looking or having jobs expands from L0 to L1. So there's more people looking for jobs. In other words if we went from yesterday's equilibrium and then we impose the minimum wage there would be more people who were actually looking seeking jobs at those higher wages. But employers at this point would be wanting to get rid of some of those workers that they had to pay higher wages to. There are certain workers within the company that they'd like to have that they'd be willing to pay the market wage for but the productivity of those additional workers are all unprofitable and so they have to do something about that. They have to reduce the amount of labor or more particularly they have to reduce the overall labor bill that they have to pay somehow some way. Now this market doesn't represent the entire labor market it's only the low skilled part of the market it's a small part even though markets are all linked. Most importantly a graph has how many dimensions? Two dimensions. There are no jobs really out there with just two dimensions.  As a matter of fact you know UPS and the auto I think it's the auto workers or the teamsters or something they're threatening to strike and they they're trying to negotiate a new contract and it's not all about their wages. Some of it is a lot of it is it's an important issue but it's not the most important one. You know one of the ones that they're interested in that I would never think of if I wasn't such an excellent lecture on the minimum wage is they want all air conditioned trucks for all the drivers. I can believe that living in Auburn Alabama I can I can definitely believe that and of course we're abstracting away from other government interventions so we're not looking at government schools and welfare and you know other types of analysis that are relevant more generally. The elasticity of those curves can change the way I've drawn them on that graph. The supply and the demand curve are relatively elastic in other words a small change in price can give you a big change in quantity but we can also imagine any elastic supply curves for unskilled workers and any elastic demand curves for low skilled workers. The minimum wage is still going to give us unemployment it's just going to give us less unemployment so elasticity does matter to the statistical results. You know in what other alternatives do employers have in terms of can they switch it for high skilled workers can they use robotics can they use capital machinery to do the job and reduce their reliance on low skilled workers. Another thing that's shown on the graph is that with the number of workers at L1 looking for jobs or having jobs and the number of jobs available L2 it means that we have a whole lot more people interested in working at that minimum wage than there are jobs and so it's at this point where employers get to discriminate you know they might hire just people from their family they might just hire people from their church they might hire people based on sex or race or hair color or what kind of car you drive anything can come into play here and does employers will now find high skilled labor and production techniques to be more profitable than low skilled high school oriented production techniques so not surprisingly unions pay the biggest portion of the the pro minimum wage propaganda effort okay somebody's got to pay for that right somebody's paying I get a newsletter every week from a group that's basically financed by unions and so everything they write is slanted in a pro union high wage minimum wage direction and then underneath this as part of the economic analysis we derive from that that the minimum wage can impact the number of hours that you work it can affect how employers set up different shifts eight hour shifts is standard but four hour shifts three hour shifts five hour shifts are all possible the minimum wage affects your benefits do you get health care do you get retirement do you have to pay to clean your own uniforms you know all sorts of different things that can come into play and then working conditions I mentioned the you know the poor ups drivers who have those old trucks without air conditioning well that's working conditions folks that's part of the job that's one of the dimensions that's part of the labor contract okay in terms of statistical obfuscation of course the Austrian view and analysis is couched in terms of Ceteris paribus or Keteris paribus where we hold all other things constant and that's important that's important for statistical analysis too this is only impacts directly a small part of the market but it influences many parts of the market the minimum wage is typically increased is increased in small incremental amounts during my heyday as an unskilled worker the minimum wage was increased a half a dozen times it hasn't been increased lately at the federal level but it's been increased at the city level the local level and typically they'll say okay we're going to raise the minimum wage from seven twenty five to fifteen dollars an hour but they're going to implement that over an eight-year period so the incremental increase is typically very small still today and so the amount of Q the quantity of labor is really all of those factors puts the Q up in the air how much is that quantity going to be and then if we relax the Ceteris paribus conditions we realize that there's just really an unlimited number of things that can change between the implementation of a minimum wage law increase and its impact on the market things like an increase in the demand for labor things like economic growth things like price and wage inflation more generally and the natural impact that that's going to have on unskilled labor so if we look at the impact on the job we find that the minimum wage causes a combination of the following and this is not an exhaustive list it's just sort of a top five list it distorts employment it can result in fewer jobs but it can also result in fewer hours it can also result in fewer employers you know in the on the west coast or the left coast on the map where the progressives sort of dominate the cities out there and have put their minimum wage increases in place they're all whining and complaining oh my favorite restaurant went out of business and big big surprise who has the hardest time dealing with a minimum wage increase aunt fanny's country cabin kitchen out in eastern oregon or mcdonald's with super computers lawyers and now robot you know you take your order you walk in and you don't even see a person they've got robots okay aunt fanny's country cabin kitchen doesn't there's not going to be any robots there okay fewer hours too decreased job benefits i mentioned health insurance vacations sick days uniforms etc decreased job desirability harder work concentrated effort less potential for advancement less sanitary conditions i worked in a cafeteria food service of a hospital when i was in high school and believe me the sanitary conditions could get really bad really quite disgusting i wish i had you know an iphone back then where i could take pictures of this stuff but didn't do that less lighting less air conditioning less everything okay you can you can imagine lots of things being impacted by the job or lots of things about a job that can be impacted okay so this is reality and it's understandable from the theory that you know the theory about price controls affecting distorting disrupting the labor market and on the two-dimensional diagram the only result possible is unemployment when we relax that assumption and we consider jobs as multi-dimensional we realize that all of these things are likely to happen and then comes along david card and alan kruger in their 1994 publication i think that was actually the working paper in 1994 um nber um alan kruger was a prominent economist i think at princeton and he was a high official in the labor department in either the clinton or the obama administration card won the nobel prize um and their study looked at the minimum wage law in new jersey and pennsylvania and new jersey and pennsylvania um you know they share a border and pennsylvania stayed with the federal four dollar and twenty five cent minimum wage in 1994 new jersey raised theirs to five dollars and five cents card and kruger took a sample based on four hundred or so fast food restaurants that were on that border or close to that border between those two states and so they declared this a natural experiment and economics doesn't really have experiments like scientists um have where they can determine in a laboratory you know how many seeds will grow out of a pack or how long will light bulbs last you know when they tell you something about the product they basically tested it in some way and found out that yes 99 of our light bulbs last for five years at least five years and so they can test these things kind of in economics we don't but this was a great anomaly that impacted the profession and shifted all of our pro-government friends in the economic profession to change their view on the minimum wage so there was a um increase in the number of minimum wage jobs in fast food restaurants in new jersey but of course this doesn't take into consideration the time the locations the differences in the economy the differences in substitution that might occur in restaurants such as um in new jersey they may have used fewer high skilled workers like managers and cooks and more low skilled workers um to do more a higher percentage of the overall work including cooking uh doesn't take into consideration cross-border effects where unskilled workers might commute to new jersey can you imagine you're living on the pennsylvania border you're living in philadelphia and the government says well you know you can go from 425 to 405 if you drive across the border and work for mcdonald's there rather than working for mcdonald's in pennsylvania so there's substitutions and there's been many many replies and criticisms of this study but i'm not going to get into them i will point out a study by hoffman and trace published in 2009 that showed that the 1996 increase in the minimum wage cost low skilled jobs um in pennsylvania so that this euphoric notion that the minimum wage can increase jobs should have gone out the window fairly quickly okay the next study i want to bring to your attention by mu mancade and shunko 2021 in the harvard business review they looked at uh chain fashion stores in california and texas from 2015 to 2018 and they found that for every one dollar increase in the minimum wage there was an increase in employment the number of jobs went up by 27 percent however the number of hours that each individual worker had on their schedule declined by 21 percent so there were more boots on the ground it's just that the boots on the ground were not getting as many hours per week um and this resulted in a decrease in the average paycheck by about 14 percent so even though you got a raise you lost hours so your paycheck got smaller so naturally they had to hire more people to fill it okay workers um working solid part-time jobs 20 hours or more 23 percent of them lost retirement benefits so you know the old ladies working in the fashion store um who were able to contribute to the retirement package or whatever in some way they got cut out as a result of this because their hours got cut people with 30 hours or more which is almost full time uh 15 percent lost their health care benefits because of the cutting hours so higher wages and more jobs don't necessarily make people better off in any economic way that i can think of i mean i no longer interact with a lot of people who earn the minimum wage or who are in low skilled jobs but i've heard it often enough how pissed people are when they don't get the same number of hours or they're required to work the night shift instead of the day shift or the day shift instead of the night shift that's what people bring to my attention so it matters and it matters in an important economic way that is not a way that's raising our standard of living or raising these people's standard of living it's hurting these people okay and i'm going to turn to an important study by numark and nizlova 2007 they studied youths ages 16 to 19 and compared them to ages 25 to 29 and found these long run effects quote exposure to minimum wages at young ages or minimum wage dominated markets at young ages could lead to adverse long run effects via decreased labor market experience and tenure okay so the most important thing you you learn a lot of important things doing unskilled jobs they really are very important it's something that employers look for it's a foundation that's very critical to your overall career just like grade point average or internships the evidence so market experience tenure and diminished education and training the evidence suggests that as individuals reach their late 20s they earn less the longer they were exposed to a higher minimum wage at younger ages and the adverse longer run effects are stronger for blacks such longer run effects of minimum wages are likely more significant than contemporaneous effects on use that are the focus of research and policy debate so what they're saying is that you know the focus on of most minimum wage research in the policy debate they're really only looking at the current market they're not looking at what happens to these people over the long run and what happens to these people over the long run is detrimental to their long run career success they may be hanging out with the wrong people they may be just hanging out with people who don't have a job and hanging out with people who have a job turns out to be with even if you don't have a job you still are better off than hanging out with people who don't have jobs ah um this was supposed to get cut out but we do have two minutes so can you read this in the back okay so i can't just make up whatever i want okay this is the average unemployment rate of EU countries european countries with and without minimum wage laws so there's a subset of european economies with minimum wage laws and there's another subset of european countries without minimum wage laws okay and this only looks at from 2004 to 2012 but i'm sure it's relatively consistent over the long run is that countries with minimum wage laws is the red line that doesn't work okay uh this is the red line it's higher this is nine this is nine percent right uh the blue line is countries average unemployment um with uh where countries without the minimum wage law so a lot of eastern european countries but not exclusively the eastern european countries their unemployment rate is about 7.3% and it's consistent throughout this whole time period it actually gets the divergence gets worse over time where the minimum wage countries have much higher unemployment 12 compared to the non-minimum wage laws countries which is 8 and of course young adult unemployment is a huge problem in europe it's a huge problem in china right now it was a big a part a big part of you know the egyptian uprising and you know a lot of these other countries is they've got this huge population of young adults sometimes young college graduates and they don't have any jobs they don't have any work experience they don't know what to do they don't have a lavish student loan programs in most of those countries but you know that young adult college graduate uh that's a really intense problem you want people getting into the workforce getting started gaining that experience developing over time any disruption to that whether it's as if you're 16 21 24 28 those disruptions are very detrimental to um people's long-term economic job outlook and i'll uh i'll show you my other slides but i'm out of time so thank you very much


first heard Bishop T. D. J. speaking about 25 years ago. I was of course very inspired by him, as were many others and still are. But I knew that his effect on my life was deeper than inspiration. I knew that he was influencing me. And influence is a challenge because influence doesn't come with instructions.  But you're not always sure what it came to teach you. And so I became a student of Bishop Jakes for several months because I didn't want to settle for being inspired, which often becomes copying. I didn't want to become another karaoke version of him as many were becoming around the world at that time. I thought there's something more valuable to me that's been modeled in his communication ability than just being inspired and kind of balting bits of him onto me that would have been very inauthentic of course, and is when people do that. And I took three things from his craft, his storytelling, his eloquence, and his angles. These three things I determined 25 years ago that I would become brilliant at myself. And so I became a student of those things. And I worked very hard for the past two decades plus to master the art of storytelling, commit to the rarity that is eloquence, and to dig deep for angles in topics because the freshness of whatever you speak about is never in the topic. It's in the angles you find within it, but you have to dig for them. These three things and much, much more I am teaching you about in my online video course called the Communication Masterclass, which from today is on offer for a massive 60% off. Grab it while you can, details are in the link in the bio, and I hope perhaps I can become an inspiration, maybe an influence in your communication journey too. Love you guys, thanks, speak to you soon.


Welcome to Toffy TV. It is the Premier League show. The second week of Premier League action has taken place and it still feels a little bit weird. It still feels very early on. Lot of teams are still bringing players in. I think 17, 18 teams will still do business between now and the end of the window. So, it's still very, very interesting what's going to happen. This weekend, week two, we have our first big game, I think. Chelsea took on Tottenham and it was a, it was a fiery game, wasn't it, Ned? Yeah, obviously the first two teams from Finish Top 4 played each other. I think that what you could say for the two teams, Chelsea have even said themselves, they don't feel like they've finished quite in the transfer market. They've still quite not, they never had the best pre-season. So, I think for them, obviously they've got a good three points. You know, in the first game, I don't know whether they'd be happy with a point. I think they were just hoping not to lose because Tottenham obviously got transfers done quite early. They look a bit more ready for the season. Obviously they've got Michalis and he's a good player. They've got players like Bersuma and they've got the lad from Inter. They're just looking really good and they looked good on the weekend. They obviously brought it back and got themselves a point, which I imagine they'll be happy with. Well, to be honest, I mean, Chelsea dominated the possession and I thought for long spells of the game looked very, very comfortable but Spades ended up having more shots on target. They've come from behind twice. Kane got the equaliser at 90 plus six, so for them it will feel like a bit of a moral victory. Obviously we all know what's happened. It was a fiery affair between the two managers, Conti and Tushal. And obviously at the end of the game, the handshake which will go down in Premier League, folklore, spark, a big, not a brawl, obviously, but it did spark a big kerfuffle, let's say, at the end. And it all just added to it a nice spice. I really like when these two teams play each other. I think it's got a lot more spice than actually the North London Dabi did and does sorry. I just think there's something that both of them have got a little bit of an edge to it. I don't think really Arsenal have got that edge. I think these two have. And I think it really played out in a really interesting fashion. I think Chelsea will be the more of the disappointed team because they were winning twice and reached James scoring the goal with 13 minutes to go to make it two on. I think they'll be really, really disappointed, but one of the players that we got to see make the debut of a player that's close to our hearts was obviously Rich Charleston. He came on, he made a bit of a difference. Over on 888 Sports YouTube channel on the playlist show, they've been having a little chat about Rich Charleston. Isi Senchenco going to be the difference of Arsenal getting top four or will Rich Charleston over the course of a season be a difference? That experience. I actually think he could be. Not to the level of a child. You know what? You know what? You say that. They've already got top four. Hold on, hold on, hold on. Let's have this one. Tottenham just got top four without this guy. Yeah, but it's going to be harder this year. It will be harder this year. Arsenal last season, when Keir and Tini was out, they played Noon of Tabaras and then they played Jackalip. Now they've got the left wing for the whole season. You've got a guaranteed versus the guide. It's just going to come in when Culler's Eski might get a bit tired. No, but it's about the games where you need something extra. You've got someone that's quality. Yeah, the other option. And bring someone off the bench that can offer something different rather than someone... What Rich Charleston will do for Tottenham? What Rich Charleston will do for Tottenham? That's why this is close. I'll tell you what Rich Charleston will do for Tottenham. Rich Charleston will turn defeats into draws and draws into wins. That is what he will do for Tottenham. But you've gone too far. You've gone too far. Rich Charleston is well capable. You bring Rich Charleston on with 15 minutes to go when you're drawing 0-0. Nick a winner. Five subs now. Well capable of doing that. Interest in hearing other people's perspectives on Rich Charleston. I still don't understand why more people don't give him respect. The guys over there on, as I said, AT&T Sports YouTube channel, talking about the five most important signs of the summer. I do think Rich Charleston will be in one of them. In this game, when he came on, he didn't make lots of things happen, but he just gives space that little bit of extra unfight to us. And when people say, well, where will he play? I think that this showed you a little bit of, he can become a little bit of a nuisance and it might free up a little space for other players. And certainly when he came on, I thought space looked much better side. Yeah, I did. I think last season with Spurs, obviously they got the top four, which was a good achievement. But I think you watch Son and Cain, they're such a good partnership, they score so many goals. When you lose them, I know they brought Culevewski in January, but you lose one of them strikers or both of them. Then they haven't really got much else on the side. I think with Charleston, it takes pressure off them doing all the hard work because he's a worker, so he really compliments talented players. And he's got qualities of very talented players himself, but his biggest quality, I think, and his biggest asset or trait is probably his work ethic and how hard he works. So I think he really compliments the more talented players on that side. Obviously they've got Champions League, they'll be wanting to finish top four again, and they've got loads and loads of games to play, so it's not like he's not going to play. Go and check out the rest of that video over on 888 Sports YouTube channel. Make sure you leave them a comment and subscribe if you haven't already. So, good draw, good firey little episode. Obviously it was the 30th anniversary of the Premier League starting as well. It all played into it and it was a really, really good faced game of a couple of the big hitters. And obviously we're going to get another one this weekend when Liverpool travelled to Manchester United. But before we trouble those three teams, Manchester City played Bournemouth, 4-0, win, very, very comfortable, no issues at all for Manchester City. Although the only surprise was Harlan never scored, Gundawand, De Bruyne, Foden and Ongol from Lema. Easy day at the office wasn't it for Manchester City? Yeah, I was watching Sky before the game and talking about Bournemouth when I'd been more of a physical team and had to beat, but City absolutely destroyed him.  Outside of the life foot. Obviously Harlan had the assist for the first goal, but that shows that he can play his part without having to score a goal. Harlan's not going to score every week. Harlan obviously gives them those extra chances. Someone he can play the ball in behind, he can switch it, he can go along. He can put balls into the box to get on, rather than trying to pass it away into the box. He's not scored every game, but he scored two in his first game. I don't think that's going to be an issue. They took the three points and Liverpool could only draw with Crystal Palace on Monday night, a 1-1 draw. Four points to gap and when you think about, I'm not writing anyone off, not writing Liverpool off, but when you think about the gap last season, four points, that's huge already. When you think about how many points Man City dropped, so Harlan got the goal on 13 minutes for Palace, good goal, and then Liverpool obviously had Nunes sent off for a head ball. He'd been getting wound up all game and ended up falling into the trap, but then Liverpool got an equaliser, fantastic goal from Diaz. Palace had chances to finish it, Liverpool had a couple of chances as well, but Liverpool would be very disappointed with their start and now that they've got injuries, but it's only taken two points in the first two games. I thought they brought a couple more plays in, to be honest by now. The start they've had, obviously they've dropped points. City's got a really good start, so it won't be good for them. I'll be looking forward when they've got injuries, jotters out, I think Fominio's out, Canati's out for them. That's not the game like Nat Phillips, I don't know what they'll play on. Obviously Nunes, I think his problem is getting wound up by a striker and if you're playing for a team like Liverpool, a big club, you've got to be able to deal with that and you should be above that. You learn those sort of mistakes at the club before going to something like that. He's going to Liverpool and it's not professionalism.  You miss the big chance as well in this game and listen, again, not going to write them off by any means, going 20 or goals this season.  To Anderson as well. Disgusting and anyone who doesn't think it's disgusting, I just did it basically so. There you go. That's what he saw, one of the biggest shocks in Premier League history with Manchester United going to Brenford. A lot of people saw Manchester United the week before playing Brighton get B21. They went to Brenford and Brenford can be really good at times, other times maybe not, but the first 35 minutes Brenford have absolutely blown Manchester United away scoring.  There is so much work to be done and Manchester United are in a position where they've got two weeks now to effectively bring in what seems like an entire team and there doesn't seem to be any kind of structure or anything to what they're doing and this was a huge, huge... Do you think it was a four-nil game? Do you absolutely deserve to be four-nil? The sad thing is though, you know he said it's one of the biggest shocks after watching it, you're thinking it doesn't feel like that much like if it was Liverpool or something on your city you think, yeah, fair enough but I've seen a lot of Gary Neville doing a lot of moan about the ball everything he says is absolutely right the glazes haven't got any sort of footballing idea of what they're doing, the wrong people in charge but business people in charge of football but you watch the team selection doesn't help at all having Fred sitting in front of that back four with Ericsson and Fernandez I don't think Ericsson and Fernandez certainly in the midfield three one of them was a number ten I don't think they work in the same team together they tried to play out the back with the way they set up the centre backs were both marked Ericsson's got a player basically grabbing right behind his shirt basically under his shirt and he's playing it into Ericsson that's not how to play out the back they just don't look like a team at all the first two games they haven't looked ready at all the first game Brighton looked like a team that I've basically just carried on from last season they looked so much so much more ready for the Premier League same with Brentford they were organised they got at them and they deserved the win they played funny enough they played two teams that their philosophies and styles on the pitch and off the pitch of what they're doing are a million light years away from what we're Manchester United are and it's just pathetic that those two football clubs Manchester United are supposed to be football clubs of English football or European football or Well football but they're so far behind on what is happening in football it's incredible and these two results prove that and sometimes that doesn't always work in football but that there's a real there's a real irony to Manchester United losing these games but it's really good as well it shows you that football isn't all about money and it's about making the right decisions and sometimes you can't throw just throw money at situations you have to have a plan you have to think it out, it does take time you have to be able to be in plays and that can go with your plan so one of the biggest upsets I think in Premier League history I mean it shouldn't be on paper because Manchester United are trash but I'm just thinking in terms of changing the way people perceive football teams or how football should be should be done and I think it was a I think it was huge I think if they carry on like this then I think the owners and people at the club will start to learn a bit more Well the talk is the owners are looking to sell now I thought Ralf Van it would still be there in some sort of spot and I would say it's for the club Well no because he sacked him because he told the truth he told the truth everything he said was the truth and they sacked him for it and the other team involved in I suppose the race for top 4 is Arsenal they beat Leicester 4-2 James got his first couple of James he says he's got his first couple of goals for them Jakar and Martin Eili Leicester stayed in it after when Arsenal were tuning up they got a goal after they went 3-1 up they got a goal but every time they scored so Arsenal had a great start a couple of wins Leicester just one draw from the two games they haven't bought any players talk of them selling plays that's going to be very interesting in a couple of weeks next couple of weeks to see they've got good players still and I think they'll be fine this season but at the moment there's no money getting invested into the team for them so that's really that's one to watch in the next couple of weeks Yeah I think Arsenal as well in terms for them I'm keeping my eye on them I still think that the team that finished top 4 is still above them in terms of being able to get back into the top 4 again but Arsenal you can see what the progress in every season I think that his ooce now is what they've been looking for or what they missed last season to be honest that could have bridged those points and get them into the top 4 they've got a proper strike and I'll play week in week out someone who wants to be the someone who suits their style of play I still think they're probably a little away from top 4 but they've got like the older guard he's coming really good now he creates a lot of chances, he's a good player the youngsters are only going to get better and better because like I said they're the only young guy In the other games a fantastic win for Norton and Forrest beating West Ham 1-0 very very fortunate to get the win in this but they've got it West Ham missed the penalty they hit the bar the goal this allowed so Forrest off with a good win that'll settle them down a little bit it's a huge 3 points for Forrest because obviously they've brought 16 players now with the latest signing so they've still not got they've got a team there that's barely played with each other they're trying to still get plays through the door a lot of them haven't started they didn't even start with a plays like Emmanuel Dennis didn't even start on the weekend so for them to get 3 points this early they'll be looking to get as many points as they can get so good for them obviously the early kickoff on Saturday was Villa beating Everton 2-1 disappointing for that good win for Villa getting near first 3 points Everton nearly managed to get to 2-2 but obviously they couldn't so that'll calm Villa down a little bit and the other games Leeds will be disappointed they were 2-0 up at Southampton Southampton called that back to 2-2 that was almost the perfect start for Leeds United getting it but Southampton brought a couple of subs on and changed it and again that will settle Southampton down after they lost obviously on the opening day so that will settle then down after a heavy defeat against Tottenham on the opening day so that will calm then Leeds will be disappointed they couldn't hold on Wolves went to Wolves tried to play the home to Fulham Wolves lost first game of the season as well but they were looking to which missed the penalty for Fulham that could have been a perfect start for him and a perfect start for Fulham that ended 0-0 and then in the other game Newcastle went to Brighton two teams that had won that opening game that ended up being a 0-0 draw after pretty much Brighton dominated the game it was basically the goalkeeper Nick Pope that kept Newcastle in the game I'm looking at Brighton Newcastle has two sort of similar teams in terms of whereabouts I think they'll be in this season both good teams, both have got good coaches they both had good starts so I think for them I'd just be happy not to lose that sort of game There you go, second week of the Premier League is over as we go into the third week this weekend Games will come for Monday night Manchester United at home to Liverpool which is going to be a huge one It will be interesting to see how both teams have had a bad start and Manchester United will be thinking well if we beat them we go above Liverpool that would be a little psychological boost other big ones Manchester City go to Newcastle that will be a very interesting game Chelsea go to Leeds as well that will be a really tough one for Manchester City going to Newcastle Newcastle have had a good start they're backing themselves pretty much that will be a really interesting one so there you go, make sure you go and check out the rest of that video on 888 Sports YouTube channel check it out, the link is in the description and watch the rest of the playlist video there you go, we'll be back next week at the Premier League show see you later


We already talked about spreadsheets and images. How about text? Could we extract any meaningful information from a set of documents? Of course we can. First, we need to install text add-on. Go to Options, Add-ons and select Text. Restart orange for the add-on to appear. Now, let us load the data. Place corpus widget on the canvas and open it. Go to Browse Documentation corpora and load green tails selected. We have 44 green tails on the output of the widget. What are these texts about? Connect corpus viewer to corpus. Corpus viewer displays text and enables us to browse it. For example, we can output only those documents that contain the word king. Another widget for visualizing the text is WordCloud. This widget displays word frequencies in a cloud. The more frequently the word appears in the text, the larger the word will be. But our WordCloud shows silly things such as punctuation and uninformative words. We will use preprocessed text to get rid of these. This widget will transform all texts to lowercase. Next, it will convert text into individual words and omit the punctuation. Individual words are called tokens. Finally, it will filter out stop words. The effects of preprocessing can be visually explored in the WordCloud. After preprocessing, this visualization looks much better. We retained only meaningful words and now we can better understand what our corpus is about. Green tails talk about kings, fathers and wives. But some words are still a bit annoying such as could, would and said. We can filter these out as well. Let us write our own custom stop word list. Open a plain text editor and type each word you want to filter on its own line. Then save the file and load it next to the preset stop word list. The changes are now propagated through the workflow. And the words we defined in our stop word list no longer appear in the WordCloud. Preprocessing is the first and a very important step in text mining. We defined our tokens and filtered out the bits we didn't need. Now our text is ready for the next step. In the following video, we will use preprocessed data to find interesting groups in green tails.


It is great to have you with us on this edition of the WB Mason post game Bob Lorenz, John Flaherty, Jack Curry with you as the Yankees win game two of this three game series, seven to two. So they've won the first two on this night. It was the ace Garrett Cole getting his second start of the season and it's nice like tonight where Cole should be spelled with a K. It was amazing, Bob. It was one of those nights where we talked about it during the cut in that when you're starting pitcher, you're only going to have a handful of these all year long where you know you have all four of your weapons, you have control and you have life. And with all that being said, it's going to end up as seven shutout innings, 13 strikeouts.  I still have to dominate. He got in trouble in the first inning. And once he got past that, it was all over. But that's why Cole is the pitcher who he is, because if there is a hiccup, if there is an obstacle, he figures out a way to get around it. And we all have dreams and even elite pitchers have dreams. I think when Garrett Cole dreams about going out on the mound, this is the kind of night that he wants to have, not just because of the stats that John just mentioned, which by the way, there are also 27 swings and misses in 97 pitches. But because he did have everything working, no matter what pitch he turned to that pitch produced for him, including that changeup, which is clearly becoming a big weapon for him this year.


Charge it! Alright, you're alive! Good job, goodbye. What's wrong, Steve? Clear? I'm safe. It's one there. Let's pull it over this. Make sure you grab your five first.


I'm Melissa Santos. I'm a data analyst at a little company, and I love box plots. I love them a whole lot. I use them a whole lot. I realized while talking to someone else earlier in this conference that I don't like a lot of other visualizations. So it's really surprising that there's one that I really love. But this is it. This is the box plot. They make fun of me at work for it. We have meetings that are at the description as to admire box plots. They joke about how maybe I can get these results as a box plot, and I'm like, yes, you can. You can. I'm going to try. So I know not everyone is super familiar with box plots, so we're going to do an introduction and go through what they are. We're going to spend some time talking about how to draw them with computers, and then we'll just look at some examples. It's called a box plot because it has a box in the middle. Real story. True story, friends. And the box has the median in it, and so if you're showing someone a box plot and they get nothing else out of it, just be like, that line in the middle, that's the median. Now you know where the median is, and that's a huge amount of additional information. Then the upper and lower parts of the box plot itself of the box are called the upper and lower quartiles. Sometimes they're called the fourths. Sometimes they're called the hinges. Let's just call them quartiles. They're like the medians for their halves. They're dividing their halves into half. And the upshot of that is that half the data is in the box. That gives you a measure of spread associated with box plots. We call the area in between the area, the height of the box, the inner quartile range, and it's a perfectly good measure of spread. It's probably more understandable than a standard deviation because you can tell it's the part that contains half the data. If you are so lucky that your data is perfectly normally distributed, it is about equal to 1.35 standard deviations. If that somehow makes it click better for you, but you really can think of it that way. We also have this notion of whiskers that go off the box plot, and they would go to the max and the min values if all your data was well behaved, so they don't. In order to keep them a little bit wrangled, the rules of box plots allow that the whiskers go out as far as 1.5 times the inner quartile range. So they don't necessarily go out that far entirely. They go out as far as the data does within that amount. And then anything past that is an outlier. And I'm not saying that in any kind of statistical way. I'm just saying that in terms of a box plot, it's an outlier. And ideally, if your data set is well behaved, there should be so few of them that it's worth the chart ink to let it be a mark of its own. So why do I love box plots so much? Because I have to get asked all the time, well, how many people typically do this? How long does it typically take for this to happen? And it typically kind of implies that the average is meaningful. And I don't believe in the average. I don't trust it. And I want to show people the range. And I want them to actually be able to see and compare things a little bit better. Even when the average is, even when the data is very close to the typical value, that's important information to know. And that's not something you get by cutting the average itself. And so again, we get the range of the data. And we get the full range of the data in a box plot. And hopefully, your data is pretty well behaved and it doesn't have a lot of outliers. And maybe you'll have a really boring box plot. And that should be wonderful and reassuring. Wouldn't that be great? But if you don't have a really well-behaved box plot, then you've learned something. And that's even better. If you find out that your data has all these wacky outliers and you have somebody who took 2,000 days to do something, you wonder what's up with them. And while we didn't see it in the example so far, one of my favorite things about box plots is they make it really easy to compare groups. You can, instead of just comparing the average or the median, you actually get to compare where the bulk of the data sits and get a feel for how the distributions differ. So let's talk a little bit about how to draw box plots with computers. I was so excited about this talk that I've been excited about it on Twitter for like two months. So I've had a lot of lovely input from people. And this is just one thing somebody sent me. Vega is an HTML canvas plotting library. And it draws these nice elements. And Altair is a Python wrapper for it. So there's just a ton of tools out there that can be used for box plots. We're not gonna get into this one. I just wanted to show there was one I had never heard of, that someone brought out to me. And before we get into the programming tools, I call these kind of the push button tools. The tools where you have a data set that you import or you get from your SQL, and then you push a button to get a graph. Tableau is the one that I see in all the job descriptions. All the job descriptions. So it must be important. So it's very good that it uses box plots. I've not ever gotten to use Tableau, so I don't know how great they are. But there's box plots, so they gotta be pretty great. Chardio is the one I use at work, and it has box plots. Thank goodness, I would have to go out to Python all the time. Someone on Twitter brought up Power BI, and I looked into it. And they don't have box plots by default, but they can be imported. Many tabs and other tool in this category that I used in school, and it has box plots as well. If any of you know of other push button-y tools that have box plots, I would really love to have a more comprehensive list of these. Because part of this is to try and make using box plots more accessible to other people. So I have a nice example data set to show you. I used Google data set search, and I found this Pokemon data set on Kaggle. All you need to know about Pokemon, and this is just the video game data. I don't know the specifics. As they come in various generations, and they have a variety of stats. They have speed and defense and attack and whatever. You can add those up and get a total stat that tells you how cool your Pokemon is. So let's do that and look at some of those stats with Python. Basic Matpotlib is very happy to give you a box plot. You just pass it any kind of vector, and it says, sure, here's your box plot. The total score for all Pokemon has a median around 450, a max around 800, and a min around 200. Here you go. Here's a box plot. Pandas has a built-in box plot method so that if you have any data frame, you can tell it to do a box plot on it. And not only can you tell it to do a box plot on any one column, you can tell it to divide up by any other column that it knows about. So in this case, we divided it out by generation. And we see that for generation one, there's one outlier, and there's one really cool Pokemon in generation one that everybody wants to get. And then we can see a little bit that the range for generation three is wider than for any of the other generations, or that the median for generation four is maybe a little bit higher than some of the other ones. If we want to get fancy, then we can use Seaborn, which is built on top of Matpotlib and is delightful, as well as having our x-axis with the generation values and our y-axis with our total score. Now we can also have a color variable, so the hue is set to the legendary type of Pokemon. So obviously, legendary Pokemon are going to be better, and the statistics reflect that. Our outlier in one is swapped up in the legendary group, and you can see that the legendary ones are uniformly much cooler scores. And then we start getting into variations on the box plot. A notched box plot has this little waist that tells you where the 95% confidence interval is for the median, which I love it. Like, I've been talking, I saw that four looks like it's a little high in that median, but then when you actually have that confidence interval to compare to the other confidence intervals, you're like, yeah, that's actually a little bit of a difference, that's for real. And so ideally, they have that beautiful shape that the blue ones have, where there's just a notch in the waist of the box. But in the case where the legendary ones or the median is at the bottom of the box, sometimes confidence interval has to extend out past the box, and you get this sangle-tooth pattern that you see here. And of course, we can do all of this in R. Base Graphics is very happy to do box plots for us. And it immediately lets me split things up immediately, just with the generation and the legendary all in one go. And then not only can I do the notched box plots in R, but I have a new function called variable width, which lets me have the sizes of the boxes be proportional to the size of the dataset. So for instance, here we see that the legendary ones are all... There's many fewer legendary Pokemon than regular Pokemon. Seems pretty reasonable. I like far width so much I had to show you another example because I really love it. So I just wanted to show you that, for instance, there are far fewer flying Pokemon than there are normal or water Pokemon. And as a glance, you can tell that the median power of the flying Pokemon is pretty good. And of course, you can do all of this in GigiPlot too as well. There's a GM box plot, and GigiPlot is perfectly happy to do both notches and far width. So I work at a little company that does organizational chart software. And so I count a lot of things about how many people... How many people report to one manager? How many... Just how many people are using the tool yesterday? How many people did anything? So I just do a lot of counting. And then I have to... And then I give them a lot of box plots about the counting. So I'm going to show you some examples from work. So we have the notion of a planning order chart. You can invite people to collaborate with you on your org chart. So by default, you have zero collaborators until you invite one. And so this is something I do fairly often, where I do this histogram-esque bar plot. And I also do a box plot because they tell you different things. From the histogram-esque bar plot, we can tell right away where the data is piling up and that there's a huge spike at zero. And it still shows you the range, which is very nice. But the box plot tells us a little bit more about where the median sits and the quartiles. And it also shows the range. So being able to pull out the median separately without having to guess at it by trying to add up these bars in your head is something that you gain by using the box plot as well. And then we have a game on our... There we go. We have a game on our mobile app called Who's Who. And it shows you someone's picture and you try and figure out which name goes with which picture. And we want to know how many people are playing that game and how viral it is within companies. And so someone has played this game over 600 times. And then I wanted to show you the screenshot from the bottom is a hover over the same box plot from the maximum Who Count. Chartio has this convention that it says the maximum and the minimum are the ends of the whiskers. And then it just calls everything else an outlier, but it does not call them the maximum or the minimum. But partly I wanted to complain about that convention and partly I wanted to show you that this tool lets me hover over any of these graphs and quickly see the median and the quartiles. And sometimes we're not just counting things. Sometimes we turn things into percentages or other kinds of metrics, and they still can make sense to be a box plot if you have a whole vector of data. So in this case, we've looked at how many people in the company play if at least two people play. Trying to get it how viral it is. And it's not really taken off. That median is pretty low. Even at the most engaged companies, only 40% of people are playing the game. But it's a lot to ask for. Another thing I do periodically is I use a logarithmic scale. And it takes away a little bit of being able to see the IQR and get what's going on with that. But it stretches out the bar plot a little bit. Box plot a lot. So you can see where the median is if it's all squished up at the bottom. As you're kind of seeing, a lot of my data is highly left skewed. It's all squished up at zero and one. So being able to see the median on something like this and still see the upper quartile and everything and then just see, oh, it does go out past a thousand. Geez, that's a lot of nodes before they first get to share what they're doing. They must be doing some kind of cool import or something. Sometimes the logarithmic scale isn't enough to save us. Sometimes we're just dominated by outliers with this highly skewed data. This is the days between signing up and using a CSV import. And so 60% of people use one on the first day. And then it goes out and out and out. And so the first box plot is obviously useless. It does nothing for us. It's just like we have a mess of outliers. The second one tries a little harder, but all it tells us really is that the median is there at one. Or at zero, rather. So in this case, I finally had to give in and use not a box plot. I had to use, sadly enough, I used a cumulative percentile graph to try and show this data. Taking a little bit of a turn, I'm back to the Pokemon data. This is the speed of the Pokemon by generation. I want to complain about bar plots. I don't see the point of having a bar plot to show on average. I feel like it implies something about the height, that fully filled in bar, implies something else about the height. It's nice that they have the error bars for the 95% confidence interval, but it tells you so much less than the box plots telling you. The outliers that are visible in generation three, the minimum of generation six being higher than the minimum on any of the other ones, all of these are things that are really easy to see with the box plots, but completely obscured by the bar plot. But I guess a table of averages didn't look cool enough. And I won't admit it, box plots aren't perfect. Even though I had an example where I had to give up already, this is some really cool research out of Autodesk where they did an entire paper of trying to fool statistical methods. And so the box plot was not the only thing they broke. And they broke the box plot by grouping the data in all these various ways. And so you have these buildups of data in different places. So what it showed me was that the box plots are really not useful at telling you where your multimodal data is. If there's multiple peaks, that's just not something it's going to communicate to you. Which it didn't really imply that it would. So I'm not too upset. The violin plot is a new version that is an extension past the box plot where we showed the density on either side of the line instead. And it's a little nicer for that, but it's a little harder to read in other ways. Like I don't know where the medians are on these. Box plots, they're wonderful. I love them. There's so much more than a central tendency. And more importantly, you can slice and dice your data a lot of different ways and see those groups and see the differences really quickly and easily. Even if you're not expecting outliers, you're going to be able to have them show up really quickly for you. And you can make them in a lot of different ways. So I love the box plots. I hope you were not too bored hearing about my enjoyment of them.