However, these assumptions are inappropriate for many types of response variables.
Often the response variable may not be continuous but rather discrete.
In regression problems, the explanatory variables are often fixed, or at least observed with more control than the response variable.
This is sufficient to determine which explanatory variables have an impact on the response variable(s) of interest.
The transformed response variable is constructed to measure the spread in each group.
The plan further calls for measuring a response variable on each wafer at each of 9 sites.
More generally, R is the square of the correlation between the constructed predictor and the response variable.
This assumes that the errors of the response variables are uncorrelated with each other.
The two variables form a joint distribution for the response variable ().
"The data from the trial have yet to be audited and information on other response variables have not been analyzed."
