# Statistics and Statistical Programming (Winter 2021)/Problem set 3

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< Statistics and Statistical Programming (Winter 2021)

Revision as of 10:39, 3 January 2021 by Benjamin Mako Hill (talk | contribs) (→Programming Challenges)

This page is a supporting page for the course Statistics and Statistical Programming (Winter 2021). |

## OpenIntro Excercises[edit]

- Complete
**exercises from OpenIntro §2:**2.12, 2.13, 2.16, 2.20, 2.23, 2.30 (and remember that solutions to odd-numbered problems are in the book!)

## 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 first*COM520 R Tutorial #2*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.