Levene's Test for Homogeneity of Variances Calculator

Use this calculator to perform Levene's Test for Homogeneity of Variances, a statistical procedure to assess the equality of variances among different groups. This tool is designed for statisticians and researchers who need to validate assumptions for various statistical tests.

Calculator

Results

F-Statistic: N/A
P-Value: N/A

Data Source and Methodology

All calculations are based on the methodologies outlined in the authoritative source: Stats Kingdom - Levene's Test. All calculations adhere strictly to the formulas and data provided by this source.

The Formula Explained

The formula for Levene's Test is defined as follows using LaTeX:

\[ F = \frac{\left(\frac{N-k}{k-1}\right) \times \frac{\sum_{i=1}^{k} n_i (Z_{i\cdot} - Z_{\cdot\cdot})^2}{\sum_{i=1}^{k} \sum_{j=1}^{n_i} (Z_{ij} - Z_{i\cdot})^2} \]

Glossary of Variables

  • N: Total number of observations across all groups.
  • k: Number of groups.
  • n_i: Number of observations in group i.
  • Z_{ij}: The j-th observation in the i-th group.

How It Works: A Step-by-Step Example

Consider three groups of data. Input your data into the fields and press "Calculate" to see how the calculation is performed step-by-step using the formula above.

Frequently Asked Questions (FAQ)

What is Levene's Test used for?

Levene's Test is used to assess the equality of variances across different groups, which is a critical assumption in various statistical tests like ANOVA.

How is the test performed?

Data from each group is input into the calculator, and the test computes the F-statistic and p-value to determine variance equality.

What does a significant p-value indicate?

A significant p-value suggests that the variances are not equal across the groups.

Why is homogeneity of variances important?

Homogeneity of variances is a key assumption for parametric tests like ANOVA, ensuring that the test results are valid.

Tool developed by Ugo Candido. Content verified by the Stats Kingdom Expert Team. Last reviewed for accuracy on: October 1, 2023.