Statistics and Statistical Programming (Fall 2020)/pset0: Difference between revisions

Latest revision as of 19:58, 16 September 2020

Programming Challenges[edit]

Because this is our first week, the programming challenges are setup tasks you can do to prepare you to complete future programming challenges.

PC1. Download and install R — You can do that from this webpage where you will have to choose based on your operating system.

PC2. Download and install RStudio — Download from the the RStudio download page choosing an option appropriate for your operating systems (e.g., Windows, Mac OSX, or GNU/Linux).

PC3. (a) Create and save a new RStudio "Project" ('.Rproj'). Then, within your new project, (b) create and save a new RMarkdown file ('.Rmd'). Finally, (c) write a combination of text notes and R code in your RMarkdown file and "knit" the output into HTML and PDF. I recommend reproducing and extending some of the examples from the R tutorial such as the following:

Complete an arithmetic problem
Assign multiple values to a variable.
Perform an operation on your variable (e.g., create a variable called x that contains a set of numerical values and multiply it by some other number.
Create variables of different classes and get R to tell you the class of each variable using the class() function.
Perform a logical comparison on the values of a variable (e.g., can you print the values of the <rivers> dataset that are less than 500?)
Install and load a library. Try the openintro package that accompanies our textbook.

PC4. Upload your .Rmd file and knitted .pdf file to the appropriate assignment on Canvas.

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+<small>[[Statistics_and_Statistical_Programming_(Fall_2020)#Week_1_.289.2F17.29|← Back to Week 1]]</small>
 == Programming Challenges ==
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 :'''PC3.''' (a) Create and save a new RStudio "Project" ('.Rproj'). Then, within your new project, (b) create and save a new RMarkdown file ('.Rmd'). Finally, (c) write a combination of text notes and R code in your RMarkdown file and "knit" the output into HTML and PDF. I recommend reproducing and extending some of the examples from the [https://communitydata.science/~ads/teaching/2020/stats/r_tutorials/w01-R_tutorial.html R tutorial] such as the following:
 * Complete an arithmetic problem
-* Create a variable (assign a value to a variable)
+* Assign multiple values to a variable.
-* Perform an operation on your variable (e.g., create a variable called <code>x</code> that has a numerical value and multiply it by some other number.
+* Perform an operation on your variable (e.g., create a variable called <code>x</code> that contains a set of numerical values and multiply it by some other number.
 * Create variables of different classes and get R to tell you the class of each variable using the <code>class()</code> function.
-* Install and load a library. Maybe the <code>openintro</code> package that accompanies our textbook.
+* Perform a logical comparison on the values of a variable (e.g., can you print the values of the <rivers> dataset that are less than 500?)
+* Install and load a library. Try the <code>openintro</code> package that accompanies our textbook.
 :'''PC4.''' Upload your .Rmd file and knitted .pdf file to [https://canvas.northwestern.edu/courses/122522/assignments/ the appropriate assignment on Canvas].