1  Assignment 1: Base R Foundations

R as a Calculator • Vectors • Data Frames • Built-in Datasets

2 Overview

This assignment introduces core concepts in base R, including arithmetic operations, object assignment, vectors, data frames, and built-in datasets. The goal is to build comfort with fundamental R syntax before moving into more advanced workflows.

You will complete all tasks in a single .R script.

3 Learning Objectives

By completing this assignment, you will be able to:

  • Perform arithmetic operations in R
  • Assign results to objects using <-
  • Create and manipulate vectors
  • Construct and subset data frames
  • Explore built-in datasets
  • Produce a simple base R visualization
  • Organize a script using clear comments

4 Textbook Connection

This assignment builds directly from Chapter 1: Introduction to R in Reproducible Research Using R.

Students are encouraged to review the chapter before beginning this assignment, as it provides the conceptual foundation and reproducible workflow demonstrated here.

5 Submission Instructions

Submit one .R script file.

Your script must:

  • Be clearly organized into labeled sections
    (e.g., # Part 1: R as a Calculator)
  • Include all required calculations and outputs
  • Include your reflection as comments at the end
  • Run from top to bottom without errors

6 Assignment Tasks

6.1 1. R as a Calculator

  1. Calculate 12 * 2.
  2. Calculate the square root of 144.
  3. Calculate 100 / 7 and round to 2 decimals.
  4. Save the result of 15 * 4 as my_product.
  5. Save 100 / 7, rounded to 5 decimals, as my_second_product.

6.2 2. Vectors

  1. Create a numeric vector of five random numbers named randy.
  2. Compute the mean, median, minimum, and maximum of randy.
  3. Create another numeric vector of five random numbers named randy2.
  4. Create randy_combined by adding randy and randy2.
  5. Create a character vector of five favorite movies.
  6. Use indexing to print the fourth movie.
  7. Create a factor with 11 entries of favorite foods (repeat some).
  8. Use table() to count frequencies.
  9. Sort the table in descending order and save as organized_table.

6.3 3. Data Frames

  1. Create a data frame called class_df with columns:
    • name
    • age
    • major
  2. Add at least four fictional classmates.
  3. Create age_in_2009.
  4. Create favorite_professor.
  5. Use indexing to:
    • Select only name and major.
    • Filter rows for Psych majors.

6.4 4. Built-in Datasets

Using mtcars:

  1. Display the first 11 rows.
  2. List all column names.
  3. Run str(mtcars) and describe column types in a comment.
  4. Run summary(mtcars).
  5. Create a base R scatterplot titled:

“My First Scatterplot”

6.5 Reflection

At the end of your script, answer in 2–3 sentences (as comments):

What was the most surprising or confusing thing you learned about R so far?

7 Reproducibility Practice

For this first assignment, focus on script organization and documentation.

At the top of your script, include a structured comment block containing:

  • Assignment name
  • Your name
  • Date
  • A brief description of what the script accomplishes

Your script should:

  • Be divided into clearly labeled sections
  • Run from top to bottom without manual intervention
  • Avoid unnecessary objects

This assignment establishes your baseline reproducibility habits for the semester.