Lab 1: Introduction to R

Introduction

Name: ___________________________

Date: ___________________________

Introduction

The goal of this lab is to familiarize you with using R and RStudio. You’ll get hands-on practice with:

Performing simple calculations (basic arithmetic, mean, etc.).
Working with variables.
Creating simple variables.

Note that this lab will all be in “base R”, meaning we won’t (yet) be working with packages like tidyverse.

Exercise 1: Basic Arithmetic

R can be used as a calculator. Try the following operations:

# Addition
5 + 3

[1] 8

# Subtraction
10 - 4

[1] 6

# Multiplication
6 * 7

[1] 42

# Division
20 / 4

[1] 5

Your turn: Calculate \(15 + 8 * 3 - 2\)

# Write your code here:

Exercise 2: Variables and Assignment

In R, we can store values in variables using the assignment operator <-.

# Create a variable called 'my_age' and assign it your age
my_age <- 25  # Replace 25 with your actual age

# Print the variable
my_age

[1] 25

Your turn: Create two variables representing the number of hours you studied yesterday and today. Calculate the total hours.

# Write your code here:

Exercise 3: Vectors and Basic Statistics

Vectors are collections of values. We create them using the c() function.

# Create a vector of test scores
test_scores <- c(85, 92, 78, 96, 88, 91, 83)

# Display the vector
test_scores

[1] 85 92 78 96 88 91 83

# Calculate basic statistics
mean(test_scores)     # Mean (average)

[1] 87.57143

median(test_scores)   # Median (middle value)

[1] 88

sd(test_scores)       # Standard deviation

[1] 6.078847

length(test_scores)   # Number of values

[1] 7

Your turn: Create a vector with the ages of 5 family members or friends. Calculate the mean and standard deviation.

# Write your code here:

Exercise 4: Creating Data

Let’s create some sample data to work with:

# Create a vector of 50 random numbers from a normal distribution
# with mean = 100 and standard deviation = 15
random_data <- rnorm(50, mean = 100, sd = 15)

# Look at the first 10 values
head(random_data, 10)

 [1] 112.02204 110.12223 119.87493  97.65791  92.04070  70.09678 110.18699
 [8] 108.63955 100.14769  86.72960

# Calculate summary statistics for this data
mean(random_data)

[1] 102.2172

sd(random_data)

[1] 15.05372

min(random_data)

[1] 70.09678

max(random_data)

[1] 134.7615

Your turn: Create a vector of 30 random numbers with mean = 50 and sd = 5. Calculate its summary statistics.

# Write your code here:

Exercise 5: Basic Plotting

R has built-in functions for creating plots. Let’s make a histogram:

# Create a histogram of our random data
hist(random_data, 
     main = "Histogram of Random Data",
     xlab = "Value",
     ylab = "Frequency",
     col = "lightblue")

# Create a simple scatterplot
x_values <- c(1, 2, 3, 4, 5)
y_values <- c(2, 4, 1, 5, 3)

plot(x_values, y_values,
     main = "Simple Scatterplot",
     xlab = "X Values",
     ylab = "Y Values",
     pch = 16,  # Solid circles
     col = "red")

Your turn: Create a histogram of the family ages vector you created in Exercise 3. Add appropriate labels.

# Write your code here:

Submission Instructions

Make sure all your code chunks run without errors
Save this file with your name in the filename (e.g., “Lab1_YourLastName.qmd”)
Render the document to HTML
Submit both the .qmd file and the rendered HTML file to Canvas