Analyzing Location and Dispersion Effects
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Minitab enables you to analyze both location and dispersion effects in a 2-level factorial design. To examine dispersion effects, you must have either repeat or replicate measurements of your response.

·    Location model - examines the relationship between the mean of the response and the factors

·    Dispersion model - examines the relationship between the standard deviation of the repeat or replicate responses and the factors

Once you have determined your design and gathered data, you can analyze both location and dispersion models. Listed below are steps for analyzing location and dispersion models in Minitab, with options to consider at each step:

1    Calculate or define standard deviations of repeat or replicate responses (Preprocess responses). Consider whether to:

·    Adjust for covariates in calculating standard deviation for replicates

·    Store means of repeats so you can analyze the location effects

2    Analyze dispersion model (Analyze Variability). Consider whether to:

·    Use least squares or maximum likelihood estimation methods, or both

·    Store weights - using fitted or adjusted variance- to use when analyzing the location model

3    Analyze location model (Analyze Factorial Design). Consider:

·    Which response column to use:

–    If you have repeats, use the column of stored means calculated in Preprocess Responses.

–    If you have replicates, use the column containing the original response data.

Here is an example: A 23 factorial design with four repeats has eight experimental runs with four measurements per run. Minitab calculates the mean of the four repeats at each run, giving you a total of eight observations. The same design with four replicates has 32 experimental runs. In this case, each measurement is a distinct observation, giving you 32 observations.

·    Whether to use weights stored in the dispersion analysis