Sample Size Determination
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Simple or Multiple Linear Regression
This utility can be used to calculate required sample size for Simple or Multiple Linear Regression to test significant deviation of effect size, R
2
, from 0.
Method used and other details
Number of predictors (k)
Required
Number of predictors in your study.
Your guesstimate of effect size. You can choose any effect size from available options.
f squared
f
R squared
η squared
Required
Approximate expected effect size, based on previus studies / pilot study. you can choose any of following four.
f squared (f
2
), f, R squared (R
2
), η squared (η
2
).
Confidence Level %
Enter positive number between 0.01 to 99.99
Required
In percentage. Commonly used values are 95, 99 and 90. Should be between 0.01 to 99.99.
Power ( 1 - β)
Enter positive number between 0.01 and 99.99
Required
In Percentage. Should be between 0.001 to 99.999. Common values are 80 % and 90 %
Sample Size Required =
@2023 Sachin Mumbare