Newbie question: Hierarchical clustering - test value (Lebart, 2000)

I am new to KNIME and I previously used Tanagra to do my clustering.
Tanagra has a nice feature called "Group characterization". Basicaly what it does
1- calculate the means and standard deviations within each group for each of the columns used
2- calculate mean and standard deviations of the full the dataset for each column
3- calculate a "test value" withing each group for each of the columns used
I was able to perform (1) and (2) (1 = "Statistics > Statistics" and 2 = "Data Manipulation > Row > Transform > Group By")
But I have no clue to how I could perform (3). The "test value" calculated by Tanagra is defined as follows (Lebart et al. 2000; p.181)
test value for a specific group and column =
( group mean - dataset mean ) / Square root of ( ( ( total number of rows - number of rows in group ) / ( total number of rows - 1 ) ) * ( variance of the dataset / number of rows in group ) )
How could I calculate such a "test value" for each column in each group of the resulting clusters ?
Thanks in advance for your answers.

Sounds like you are after something like a single sample t test. The formula you mention is rather similar.

this is available under statistics and then hypothesis testing.

does this help.