R language assignment and discussion

 

Assignment:

Now that you have R installed on your computer, you will begin to get some experience (hands-on) with the software. For this assignment, you are exposed to just 4 features of R: Arithmetic Operations; Operations on vectors; the Recycle Rule for adding/subtracting vectors; and Creating a S3 Class Object. A separate screen shot is required for execution of each feature. Open R (either command line or RStudio). Enter code that will handle the following (show all code, comment for each code line and the computed results in your screen shots). These are instructions; do NOT just write the instructions – actually show this within R and capture a readable screen shot to show that it works properly!!

Screen shot 1: Arithmetic Operations

assign a value of 144 to x

assign a value of 6 to y

add x and y

subtract y from x

multiply x times y

divide x by y

find the square root of x

Screen shot 2: Operations on vectors

create a vector (afc) and assign values 2,6,3

create a vector (nfc) and assign values 6,4,2

add afc and nfc

Screen shot 3: Recycle Rule for adding and subtracting vectors

assign values 2,1,8,3 to vector x

assign values 9,4 to vector y

add x to y

notice the warning message – use the Recycle Rule for adding vectors; then

add x to y and show results

subtract 1 from x – apply the Recycle Rule for subtracting vectors; then

subtract y from x and show results

Screen shot 4: Create an S3 Class Object

create a list – with components: name = Your name, date = today’s date, and score = score you desire on Assignment 2.

name the class as “graduate student”

Save the screen shots as a MS Word document (*.docx).

Discussion:

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)?

When replying to a classmate, offer your opinion on what they posted comparing the R programming language to the other statistical programming languages. Using at least 3 – 5 sentences,

explain why you agreed or disagreed with their evaluation of the different statistical programming languages.

Requirements: as per question

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