How to Perform Levene’s Test in Python for Equal Variances (Scipy & Numpy)
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Before running ANOVA or t-tests, you need to check for equal variances. In this tutorial, you’ll learn how to use Levene’s Test in Python with SciPy and NumPy to determine if groups have statistically similar variances—a key assumption in many statistical tests.
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In this video, I walk through Levene's test in Python and show you exactly how to confirm or reject equal variances across groups. We start with a detailed manual calculation so you can see every step of the formula, then move into two practical examples using scipy that make your life much easier. The first scipy example covers two groups using the median (also called the Brown-Forsythe test), and the second example shows three groups using the mean.
I explain when you need Levene's test—like before running independent t-tests or ANOVA—and why it works well with non-normal data. You'll see the null hypothesis (all group variances are equal) versus the alternative hypothesis (at least one group has a different variance), and I show you how to interpret the W statistic and p-value at a 0.05 significance level. By the end of the video, you should be able to confidently apply Levene's test to your own data, decide between mean, median, or trimmed mean versions, and understand why scipy makes these statistical tests so much faster than doing them by hand.
TIMESTAMPS
00:00 Introduction to Levene's Test
01:00 Why Use Levene's Test?
02:15 Formula Overview & Example Setup
03:50 Manual Calculation Steps
07:30 Python Code - Manual Example
14:30 Calculating Degrees of Freedom
17:20 Finding P-Value & Conclusion
20:00 Example 2: Slayer vs Metallica (Using SciPy)
22:40 Example 3: Three Bands Comparison
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