I'm curious about the assumptions underlying the t-test. I know it assumes that the data is normally distributed, but are there any other assumptions I should be aware of? Can you elaborate on this?
In addition to normality, the t-test assumes that the data is measured on an interval or ratio scale. In other words, the measurements should have meaningful numerical values and equal intervals between them. This assumption allows for meaningful calculations of the mean and standard deviation, which are essential for the t-test calculations.
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Yes, in addition to the assumption of normality, the t-test also assumes that the groups being compared have approximately equal variances. This assumption is known as the assumption of homogeneity of variances. Violation of this assumption can affect the validity of the t-test results.
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Along with normality and homogeneity of variances, the t-test also assumes that the observations are independent of each other. This means that the values in one group should not be related to or influenced by the values in the other group. Violations of this assumption can lead to biased or inaccurate results.
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