3/7/2024 0 Comments Xlstat add multiple variables![]() ![]() ![]() This statistic follows a Fisher’s F distribution with p and n1+n2-p-1 degrees of freedom if the samples are normally distributed for all the variables. The F statistic that is used for the comparison test where the null hypothesis H0 is that the means of the two samples are equal, is defined by:į = T² ⁄ The Mahalanobis distance can be used to compare two groups (or samples) because the Hotelling T² statistic defined by:įollows a Hotelling distribution, if the samples are normally distributed for all variables. Where xi is the vector x1 and ∑ is the covariance matrix. ![]() The square of the Mahalanobis distance writes: The Mahalanobis distance allows computing the distance between two points in a p-dimensional space, while taking into account the covariance structure across the p dimensions. It may be that two samples are different for a variable with a Student t test, but that overall it is impossible to reject the hypothesis that they are similar. Instead of comparing the average of two samples as with the Student t test, we compare here simultaneously for the same samples averages measured for several variables.Ĭompared to a procedure that would involve as many Student t-tests as there are variables, the method proposed here has the advantage of using the structure of covariance of the variables and of obtaining an overall conclusion. Multidimensional tests implemented in XLSTAT are used to compare samples described by several variables. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |