Objective

To familiarize students with the R programming environment, basic commands, and fundamental concepts such as packages, help pages, R objects, and notation.

Submission

  1. Download the Module 1 exercise R scipt

  2. Save your completed R script as: module1_lab_lastname_firstname.R

    • Ensure your Answer Sheet (reflection and written responses) is filled out completely.

  3. Check your work

    • Verify that all code runs without errors.
    • Make sure your name, student ID, and course/year are included in the answer sheet.

  4. Upload to Google Form

    • Upload your R script module1_lab_lastname_firstname.R using this Submission link.
    • Fill in the required student information fields (Name, Student ID, Course/Year).
    • Submit before the deadline

Part A: Setting up R and RStudio

  1. Install R and RStudio
    • Download and install R from CRAN.
    • Download and install RStudio Desktop.
  2. Check version
version

Part B: Packages and Help Pages

  1. Install and load a package.

  2. Install the tidyverse package:

install.packages("tidyverse")
library(tidyverse)
  • Verify that the package loaded successfully.
  • Explore help pages
  • Use the help function to learn about mean():
?mean
help(mean)
  • Summarize what the function does and the arguments it accepts.

Part C: R Objects

  1. Create basic objects

  2. Create a numeric vector

x <- c(2, 4, 6, 8, 10)
  • Create a character vector:
names <- c("Anna", "Ben", "Carla")
  • Create a data frame:
df <- data.frame(ID = 1:3, Name = names, Score = c(85, 90, 88))
  • Inspect objects
  • Use functions like class(), length(), str(), and summary() to explore the objects.

Part D: R Notation

  1. Indexing and subsetting

    • Extract the 3rd element of vector x.
    • Extract the Score column from df.
    • Extract the second row of df.

  2. Applying functions

    • Compute the mean of vector x.
    • Compute the mean of the Score column in df.