1)

This course will require R and R Studio to create some visual graphs we will be learning about this semester through the tutorials. To create graphs, you will need to install R and R Studio on your computer. Please view the R lecture below. Note that the software is free and I will provide the datasets as we progress in the course.

Here are some additional instructions to install R and R Studio on your computer: https://www.youtube.com/watch?v=9-RrkJQQYqY

Download and Install the R Programming tool (Cran), Python, and MySQL for Excel software onto your PC. Verify successful installation by attaching ONLY the screenshots to display your completion of each software installation (3 total screenshots).

Save your assignment as a Microsoft Word document. (Mac users, please remember to append the “.docx” extension to the filename.) The name of the file should be your first initial and last name, followed by an underscore and the name of the assignment, and an underscore and the date.

An example is shown below:

Jstudent_exampleproblem_101504

Also, please summarize in a short paragraph how the installation went for you. What problems, if any, did you have and how were they solved? What things went right for you during the installation?

2)R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

Why are statistical programming languages important to data scientists? What are some advantages and disadvantages the R programming language has over the other main statistical programming languages (i.e. Python, SAS, SQL)?