Uploaded November 2018 | Updated September 2026, 1 week ago
In this video tutorial I talk about conducting Hotelling's T-squared test using R.
RPubs documents is available at rpubs.com/juanhklopper/multivariate_comparison_of_means_of_two_groups
RMD and csv files are available at github.com/juanklopper/R_statistics
Hotelling's T-squared test allows us to compare a vector of means (for more than one variable) between two samples. It is a generalization of Student's t test.
In general, multivariate tests compare or predict more than one variable (simultaneously). As an example, we might compare the means of low-density lipo-protein cholesterol, triglyceride, and diastolic blood pressure between two samples. Each patients has all three of these variables measured and we want if the three of them (combined) are different between the groups. In a regression example we might have multivariables predicting more than one (multivariate) variable.
In this video tutorial I talk about conducting Hotelling's T-squared test using R.
RPubs documents is available at rpubs.com/juanhklopper/multivariate_comparison_of_means_of_two_groups
RMD and csv files are available at github.com/juanklopper/R_statistics
Hotelling's T-squared test allows us to compare a vector of means (for more than one variable) between two samples. It is a generalization of Student's t test.
In general, multivariate tests compare or predict more than one variable (simultaneously). As an example, we might compare the means of low-density lipo-protein cholesterol, triglyceride, and diastolic blood pressure between two samples. Each patients has all three of these variables measured and we want if the three of them (combined) are different between the groups. In a regression example we might have multivariables predicting more than one (multivariate) variable.
