ANOVA (f_oneway) in SciPy

Introduction

ANOVA helps us check if different groups have different average values. It tells us if the differences we see are real or just by chance.

Comparing test scores of students from three different schools.

Checking if three types of diets lead to different average weight loss.

Seeing if different machines produce parts with different average sizes.

Comparing average customer ratings for three different products.

Syntax

SciPy

scipy.stats.f_oneway(group1, group2, ...)

Each group is a list or array of numbers.

The function returns two values: the F-statistic and the p-value.

Examples

Compare two groups with simple numbers.

SciPy

from scipy.stats import f_oneway

f_oneway([1, 2, 3], [4, 5, 6])

Compare three groups to see if their averages differ.

SciPy

f_oneway([10, 12, 14], [10, 11, 13], [9, 12, 15])

Sample Program

This code compares the average scores of three classes to see if they differ significantly.

SciPy

from scipy.stats import f_oneway

# Scores of students from three classes
class1 = [85, 90, 88, 75, 95]
class2 = [80, 85, 84, 70, 90]
class3 = [78, 82, 85, 72, 88]

f_stat, p_val = f_oneway(class1, class2, class3)

print(f"F-statistic: {f_stat:.3f}")
print(f"p-value: {p_val:.3f}")

Important Notes

A small p-value (usually less than 0.05) means the groups are different.

ANOVA assumes the groups have similar spread (variance) and are independent.

If p-value is large, it means no strong evidence that groups differ.

Summary

ANOVA tests if multiple groups have different averages.

Use scipy.stats.f_oneway with groups as inputs.

Look at the p-value to decide if differences are significant.