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Levene's test

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QXL Stat Tools Tab > Hypothesis Tests > Tests for Variance > Levene's test

Test type: Variance
Data: Quantitative
Number of Variables: 1
Number of Groups: 2 or more
Assumptions: 2 or more samples from continuous distributions

Levene's test is a hypothesis test used for testing variance equality between samples of two or more populations. It assumes that samples come from continuous distributions. If the samples are normally distributed Bartlett's test is more powerful.

Hypothesis tested:

H0 : σ1 = σ2 = ... = σn
H1 : σi ≠ σj

where σk is the population variance.

Step #1: Select data source for Levene's test.

Data for the Levene's test can come from an Excel spreadsheet or SQL data source.

See source data formats and example data for the Levene's test.

Step #2: Options.

  • 'Median' or 'Mean' options (default = Median). Tells Quantum XL whether to use mean or median to calculate statistics. Selecting 'Median' option will run Brown"“Forsythe test.

  • 'Decision Criteria' option (default = 0.05). The value of the decision criteria (significance or α level).

  • 'Box Plot'option. Display box plot hypothesis results.

  • 'Display mode' option. When the 'Verbose (long)' option is on, Quantum XL will display additional text that explains the hypothesis test results.

Example

Levene's test

Quantum XL will display test statistic (L), p Value, 95% Bonferroni CI for StDevs, and dataset statistics.

In this example the p-Value is very small (2*10-7). Since it is less than the decision criteria (0.05), the null hypothesis can be rejected. We can draw the conclusion that the variances are different.

Update

Levene's test is updatable. After you create the analysis, you can change its data source or add new data to the data source and simply update the analysis.

  • Update: Quantum XL > Statistical Tools > Update Sheet

  • Change settings: Quantum XL > Statistical Tools > Modify Chart/Analysis