How to Perform a One-Way ANOVA in Python

To perform a one-way ANOVA in Python, you can use the f_oneway() function from the SciPy library. Here’s an example:

import scipy.stats as stats

# Define the data for each group
group1 = [1, 2, 3, 4, 5]
group2 = [2, 4, 6, 8, 10]
group3 = [5, 10, 15, 20, 25]

# Perform the one-way ANOVA
f_statistic, p_value = stats.f_oneway(group1, group2, group3)

# Print the results
print("F-Statistic:", f_statistic)
print("P-Value:", p_value)

In this example, we define three groups of data and then call the f_oneway() function, passing in the data for each group. The f_oneway() function calculates the F-statistic and p-value for the one-way ANOVA test. We print out the results for each.

It is worth noting that before performing the ANOVA, you should check the assumptions of normality and equality of variances. You can use various visualization techniques such as histogram or QQ-plot to check for normality, and the Levene’s test to check for the equality of variances. Also, you can also use the stats.normaltest() function from the SciPy library to perform a normality test.

If the assumptions are not met, you may need to transform your data or consider using a non-parametric test such as the Kruskal-Wallis test.