ANOVA in Data Analysis Python - Mini Project: Build & Apply

Performing ANOVA to Compare Group Means

📖 Scenario: You are a data analyst working for a company that wants to understand if three different training programs lead to different average test scores among employees.The company collected test scores from employees who attended each training program.

🎯 Goal: You will create a dataset with test scores for three groups, set up a significance level, perform a one-way ANOVA test to compare the means, and print the ANOVA test result.

📋 What You'll Learn

Create a dictionary called scores with keys 'Program_A', 'Program_B', and 'Program_C' and their respective test score lists

Create a variable called alpha and set it to 0.05

Use scipy.stats.f_oneway to perform ANOVA on the three groups

Print the ANOVA test statistic and p-value

💡 Why This Matters

🌍 Real World

ANOVA is used in many fields like business, medicine, and education to compare group averages and make decisions based on data.

💼 Career

Data analysts and scientists use ANOVA to test hypotheses about group differences and support data-driven decisions.

1

Create the dataset with test scores

Create a dictionary called scores with these exact entries: 'Program_A': [85, 88, 90, 85, 87], 'Program_B': [78, 75, 80, 79, 77], and 'Program_C': [92, 95, 94, 96, 93].

Data Analysis Python

# Create the dictionary scores with the given test scores
# Your code here

Hint

Use curly braces {} to create a dictionary with keys and lists as values.

2

Set the significance level

Create a variable called alpha and set it to 0.05 to represent the significance level for the ANOVA test.

Data Analysis Python

scores = {
    'Program_A': [85, 88, 90, 85, 87],
    'Program_B': [78, 75, 80, 79, 77],
    'Program_C': [92, 95, 94, 96, 93]
}
# Create the variable alpha and set it to 0.05
# Your code here

Hint

Just assign the number 0.05 to the variable alpha.

3

Perform the ANOVA test

Import f_oneway from scipy.stats and use it to perform a one-way ANOVA test on the three groups in scores. Store the result in a variable called anova_result.

Data Analysis Python

scores = {
    'Program_A': [85, 88, 90, 85, 87],
    'Program_B': [78, 75, 80, 79, 77],
    'Program_C': [92, 95, 94, 96, 93]
}
alpha = 0.05
# Import f_oneway and perform ANOVA on the three groups
# Your code here

Hint

Use f_oneway with the three lists as separate arguments.

4

Print the ANOVA test result

Print the ANOVA test statistic and p-value from anova_result in the format: "F-statistic: {value}, p-value: {value}" using an f-string.

Data Analysis Python

from scipy.stats import f_oneway

scores = {
    'Program_A': [85, 88, 90, 85, 87],
    'Program_B': [78, 75, 80, 79, 77],
    'Program_C': [92, 95, 94, 96, 93]
}
alpha = 0.05

anova_result = f_oneway(scores['Program_A'], scores['Program_B'], scores['Program_C'])
# Print the F-statistic and p-value from anova_result
# Your code here

Hint

Use print(f"F-statistic: {anova_result.statistic}, p-value: {anova_result.pvalue}").