Statistical Analysis with Python for Dummies by Schmuller Joseph;

Author:Schmuller, Joseph; [Schmuller, Joseph]
Language: eng
Format: epub
Publisher: John Wiley & Sons, Incorporated
Published: 2025-11-18T00:00:00+00:00

Returns:

t_statistic: The t-statistic.

p_value: The p-value associated with the t-statistic.

'''

I’m using the ANOVA table I computed earlier.

The first step is to calculate the group means and put them in a list:

means = list(data.groupby(independent_variable)[dependent_variable].mean())

Then I calculate the contrast effect, meaning the numerator of the formula:

That’s

contrast_effect = sum(contrast[i]*means[i] for i in range(len(contrast)))

Next, I start working on the denominator. I retrieve the MSWithin from the ANOVA table:

MS_Within = anova_table.loc['Residual','mean_sq']

The ANOVA table refers to “Within” as “Residual.”

Next, I get the sample sizes and their reciprocals and put the reciprocals in a list:

sample_sizes = data.groupby(independent_variable).size()

recip_sample_sizes = list(1/sample_sizes)

Then I square each contrast coefficient

squared_contrast = [i**2 for i in contrast]

The next step is to use the preceding three lines of code to calculate this segment of the denominator:

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.