How To Perform One Way Anova In Python

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One-Way ANOVA (Analysis of Variance) is a statistical method used to test if there are any significant
differences between the means of three or more independent groups. In this tutorial, we will learn how to
perform a One-Way ANOVA in Python using the SciPy library.

Prerequisites

Before we begin, you need to have Python and the following libraries installed:

You can install these libraries using pip:

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pip install numpy scipy

Example Data

Let’s say we have the following dataset, which represents the test scores of students from three different
classrooms:

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classroom1 = [62, 74, 85, 88, 90, 76]
classroom2 = [55, 70, 81, 98, 68, 80]
classroom3 = [86, 94, 88, 77, 84, 93]

We want to determine if there is a significant difference in the test scores between the three classrooms.

Performing One-Way ANOVA Using SciPy

First, we need to import the scipy.stats module, which contains the function
f_oneway() that we will use to perform the One-Way ANOVA:

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import scipy.stats as stats

Now, we can use the f_oneway() function to calculate the F-statistic and the p-value:

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F, p = stats.f_oneway(classroom1, classroom2, classroom3)

The f_oneway() function returns two values: the F-statistic and the p-value. The F-statistic
tells us whether the group means are different, and the p-value tells us how significant the differences are.

Interpreting the Results

With the F-statistic and p-value calculated, we can interpret the results of our One-Way ANOVA. Generally,
if the p-value is below a predetermined significance level (usually 0.05), we reject the null hypothesis and
conclude that there is a significant difference between the groups.

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alpha = 0.05
if p &lt; alpha:
    print(f"The p-value ({p:.4f}) is less than the significance level ({alpha}), so we reject the null hypothesis.")
else:
    print(f"The p-value ({p:.4f}) is greater than the significance level ({alpha}), so we fail to reject the null hypothesis.")

By running this code, we will find out if there is a significant difference in test scores between the three
classrooms.

Conclusion

In this tutorial, we learned how to perform a One-Way ANOVA in Python using the SciPy library. We showed how to
calculate the F-statistic and p-value, as well as interpret the results to determine if there is a significant
difference between the means of multiple groups. This technique can be useful in various fields, such as
education, finance, and marketing, to analyze data and draw meaningful conclusions.