 Statistics and Excel. Hamlet, Harry Potter, and Statistics. Got data? Let's get stuck into it with Statistics and Excel. You're not required to, but if you have access to this online OneNote, we're located icon left-hand side. OneNote and Excel presentations. Presentation number 1010, Hamlet, Harry Potter, and Statistics. We're also attempting to upload our transcripts to OneNote so that you can then go to the View tab, use the Immersive Reader tool, and if you want to, you can change the language to whatever language you so choose and either read or listen to the transcripts in that language. Desktop version of OneNote here, thinking about how we can organize data so that we can possibly extract some meaning, some information from that data. Now note that, of course, when we have different kinds of data and we have different objectives with those data, we're going to use different tools to organize the data in different ways. However, no matter the objective, no matter the kind of data we have, we would usually like to sort the data in different ways so we can get different angles, different perspectives on that data, because if we look at something from different angles, we're more likely to get a fuller picture of what is going on than if we look at something from one particular angle. Now, of course, all the angles that we look at might not be equally weighted. There might be one particular angle that we look at that gives a better picture than if we look at something from a different angle, but if we put all the angles together, that's usually going to be a better fuller picture than just one particular view. Okay, so here we have Shakespeare's play Hamlet and what we've done is we've just taken out the words and we've listed the words and how often they appear in the play. Now, first, of course, this is just simply to point out that now we have a list of data, a list of words and how often they appear. And clearly, in order to make the Shakespeare play of Hamlet, those words have to be ordered in a very particular way. So you would think that the genius of Shakespeare isn't simply in selecting the words that they use, although that would be important, I would think. But also, there's going to be a great deal of importance on the ordering of the words. If we think of the data as the words, the order of the words is going to be quite important to get to an end result like Hamlet. We couldn't just randomly put these together. Possibly ChatGTP could do it right now at this point in time, but you'd have to have some kind of intelligence, whether it be artificial or human, to put the words together in order to make a good poem or play or whatever that we are creating. However, we can also look at this in terms of another way to look at the play of Hamlet, which is often actually useful in different fields of like English and literature, for example. Because I mean, if we're able to list all the words that show up and order the words, then we can ask questions like, well, which word is it really important that Lord was the biggest word? Can we pull some meaning from the words that are here? We might be able to say, hey, well, if Lord is the word that's used the most, then possibly most of the play, we can kind of guess where the play is going to be set in a courtly kind of setting and what number of people, where there's a lot of lords around and whatnot. And then again, you can ask the questions, is that a key component to making a very memorable type of play? And you can go on different tangents from organizing this information this way. I've also seen an organization of the different kind of tropes or rhetorical tools that Shakespeare's uses as well. And so that's another list that could be quite interesting to look at for people that are trying to hone their own rhetorical skills and whatnot. They might say, well, how often does the greatest playwright use these different kind of rhetorical tools and why could be interesting? Also, there's also some cases where we don't know who wrote particular things. So oftentimes, if you look at biblical texts, they have questions in terms of who wrote this particular item, or when we go to like the people that wrote the Federalist papers and whatnot, we don't know who actually wrote particular documents. Sometimes the way they can make an educated guess about that is they can list out the number of words that show up and say, well, this particular person tends to use these words more or use these rhetorical tricks more than these phrases more than somebody else. And that can be a way for us to kind of determine who wrote what. So even something like a play, we can look at it from different angles, and we possibly can extract some meaning from it. And it depends what our goal is. What's our goal? If our goal is to say who actually wrote this, because I don't know, then we might sort it in different ways. If our goal is to say, hmm, can I look at this in different ways and try to say what else can I pull to make me a better playwright or something like that, then again, we might sort the data differently to try to understand how it's being put together. So if we take this data, then, of course, the first thing that we're going to do, usually, if we just counted all the words, it might not be in order at first look, right? It might be random scrambling of words. We might have sorted the words in alphabetical order. But then the next thing you would think you would do with just about any kind of data is to sort the data from lowest to highest or highest to lowest. So in this case, clearly, you would think that we would want the highest word. So we're looking at whatever our objective is, if it's to improve our skills as a poet, or to try to figure out who's writing what is this really written written by Shakespeare or something, we might first want to know what's the one that's going to be used the most and try to extract some meaning from that. So that's usually the first thing that we will do. Now, once you have this, it's useful because you can just look at this data and say, okay, I can get some meaning from simply this list of data. But if we had a huge list of data, then it might be more difficult to extract meaning from that data. Therefore, the next step we often do is to create a pictorial representation of the data. And I want to emphasize again and again that the pictorial representation isn't simply dumbing down the data for non non statistically minded people, because the picture is going to is going to activate another angle that we're looking at the data this picture is saying the same thing as this table and I can I can kind of extract