Statistics and Statistical Programming (Fall 2020)/pset0: Difference between revisions
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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: | :'''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 | * Complete an arithmetic problem | ||
* | * Assign multiple values to a variable. | ||
* Perform an operation on your variable (e.g., create a variable called <code>x</code> that | * 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. | * 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. | * 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]. | :'''PC4.''' Upload your .Rmd file and knitted .pdf file to [https://canvas.northwestern.edu/courses/122522/assignments/ the appropriate assignment on Canvas]. | ||
Revision as of 19:56, 16 September 2020
Programming Challenges
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
xthat 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
openintropackage that accompanies our textbook.
- PC4. Upload your .Rmd file and knitted .pdf file to the appropriate assignment on Canvas.
