[BLANK_AUDIO] In this course, we're going to talk a lot about different tools and techniques to help you make your work reproducible. And now, before we get into all that, though, I just want to kind of boil down the basic principle that we want to deal with throughout this whole course. I mean, if there's one rule that I think we would, you would want to adhere to, to make your work as reproducible as possible is that you should script everything. Scripting is really important and it's the basic idea of writing everything down. Back in the old days you might have written down, you know, things down on paper or in lab notebooks. But now that we have more sophisticated computers and we can program them, we write things down as pr, as scripts or programs. So I mean, if you, as, just by way of analogy. You think about you think about a great symphony or a great piece of music. You think of if you, if you imagine just hearing the melody of a piece of music, okay? That's very interesting, it's also can be very beautiful. But often, if you look at a symphony, there's a whole orchestra. There's a whole set of musicians that are kind of backing up the melody. And doing a lot of work and all that work is really important and contributes to the texture, contributes to the, the kind of feel of the whole piece of music, right? So if you been out and if you were just hear a symphony it probably would be difficult for you to reproduce that sound even if you could hire your own orchestra because you wouldn't know where all the notes were, what all the, all the different instruments were playing at any given time. That even if you heard it a few times, you saw, probably still wouldn't be able to do it. And you, in particular you would definitely not be able to reproduce that sound if you were to only hear the melody, right? So, if you think about the presentation of of an analysis or of your research [COUGH] the presentation is really kind of like, like hearing the melody alone, right? The melody is really nice, it's really important. But it's, there's all this supporting material that, that's going on behind the scenes. All the, the analyses that you did, all the exploratory work, all of the, kind of, dead ends that you went down, all the decisions that you made in your analysis, which are not presented in your, kind of, final presentation, whether it's a paper or a oral presentation. But they're all very important. So those are the supporting players, all right? So just like in music in research we need a way to kind of write down everything that we did, everything that's going on right? So in music this is typically called the score, right? So the score is, is, is a way to kind of write down in musical notation all the different things that are being played. All the different things that are going on. All the notes, all the rhythms. All the timings, all the instruments, everything. And so someone can look at the score and say okay, well I need to put together all these things and I, every- ever- people have to play at different times and different locations. And so it's a way to, for you to reproduce a piece of music as accurately as possible. And, and musicians have kind of, have come, have agreed upon a standard way to write down music. And a standard notation for doing that. And so this course is essentially about, you know, defining and developing the notation of specifying a re, a research project or a data analysis. Right, so what is the, how do we write down what the what are the things that we did, how did we talk about exactly what was analyzed, what was done. And so the way that we do that essentially is through scripting, right? We write down computer programs. We talk, we we give instructions to the computer and tell it what to do at any, at any given time with what type of data. And so the main rule for anything you in data analysis is to write a script. And the more you can do that and the less you can kind of do things by, on your own, by hand without writing it down, the better and the more reproducible your work will be. So this, so these computer programs, these scripts that we write. These are like the score for your data analysis. They tell someone else who's trying to reproduce your work exactly what happened and what to do. So, if you want to get a sense of what it means to script something. You can just load up Rstudio. And when you load it up, you'll see that there's, that you, the first thing you can do is you can open an R script. So, here we do that and this is just a blank text file. And then you can start writing R code in here. And then you'll be writ-, you'll be programming, you'll be telling the you know, R what to do in terms of a coding language, right? So this is your, this, this is the, the easiest way to get started scripting. Is to u, is to load up something like Rstudio and, and, and use the text editor that's built in. So, in this course we'll talk about a bunch of other tools things like Nader, things like Markdown that'll help you kind of, organize your analyses. But the bottom line is, to write it down, write a script, write a program, and make your work reproducible.
