t-test in R Programming - Mini Project: Build & Apply

Performing a t-test in R

📖 Scenario: You are a scientist studying the effect of a new fertilizer on plant growth. You have measured the heights of plants with and without the fertilizer. You want to check if the fertilizer makes a significant difference in plant height.

🎯 Goal: Learn how to perform a t-test in R to compare two groups of data and interpret the result.

📋 What You'll Learn

Create two numeric vectors with exact plant height values

Create a variable to hold the significance level

Use the t.test() function to compare the two groups

Print the p-value from the t-test result

💡 Why This Matters

🌍 Real World

Scientists and researchers use t-tests to check if two groups have different averages, like testing new medicines or fertilizers.

💼 Career

Data analysts and scientists often perform t-tests to make decisions based on data and prove if changes have real effects.

1

Create the plant height data

Create two numeric vectors called control and fertilized with these exact values: control = c(15, 16, 14, 15, 16), fertilized = c(18, 19, 17, 20, 18).

R Programming

# Create the plant height data vectors
# Your code here

Need a hint?

Use the c() function to create numeric vectors with the exact values given.

2

Set the significance level

Create a numeric variable called alpha and set it to 0.05 to represent the significance level.

R Programming

control <- c(15, 16, 14, 15, 16)
fertilized <- c(18, 19, 17, 20, 18)
# Create the significance level variable alpha
# Your code here

Need a hint?

Just assign the value 0.05 to a variable named alpha.

3

Perform the t-test

Use the t.test() function with control and fertilized as inputs and save the result in a variable called test_result.

R Programming

control <- c(15, 16, 14, 15, 16)
fertilized <- c(18, 19, 17, 20, 18)
alpha <- 0.05
# Perform the t-test and save the result
# Your code here

Need a hint?

Use t.test(control, fertilized) and assign it to test_result.

4

Print the p-value

Print the p-value from test_result using print() and accessing the $p.value element.

R Programming

control <- c(15, 16, 14, 15, 16)
fertilized <- c(18, 19, 17, 20, 18)
alpha <- 0.05
test_result <- t.test(control, fertilized)
# Print the p-value from test_result
# Your code here

Need a hint?

Use print(test_result$p.value) to show the p-value.