Could you provide an example? If I had an example for how they are used I could make a better suggestion.

For now, I'll say that variability typically refers to the variability of a single data set around the mean (i.e., standard deviation, standard error, etc.), while heterogeneity typically means a difference in the variability of >1 data set. Hypothesis tests rely on particular assumptions, and a common assumption (particularly in analyses of variance) is homogeneity of variances across the groups that you wish to compare (also known as homoscedasticity). If the variances of the groups that you want to compare are drastically from one another, then those variances are considered heterogeneous and you need to apply appropriate methods to analyze your data (transformations or non-parametrics).

Variability (measure of dispersion) attributes for single data set or within a statistics estimated for different data set.

Heterogenity is in general similar variance of two or more than two data sets or populations. Generally referred for comparative or generalization purposes.

Variability is how spread out or closely clustered a set of data is.variability typically refers to the variability of a single data set around the mean (i.e., standard deviation, standard error, etc.

While heterogeneity refers the availability of different class of data sets which are having variability in their members/elements.

Dear Feff, Rajiv, and Mritunjay

Thank you for the quick response and clear explanation. I have got it now.

zhao