Note: Within the Contingency platform, you can use the Analysis of Means for Proportions when the response has two categories. For details, see the Contingency Analysis section.
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Use ANOM to compare group means to the overall mean. This method assumes that your data are approximately normally distributed. See Example of an Analysis of Means Chart.
This is the nonparametric version of the ANOM analysis. Use this method if your data is clearly nonnormal and cannot be transformed to normality. ANOM with Transformed Ranks compares each group’s mean transformed rank to the overall mean transformed rank. The ANOM test involves applying the usual ANOM procedure and critical values to the transformed observations.
Suppose that there are n observations. The transformed observations are computed as follows:
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The ANOM procedure is applied to the values Transformed Ri. Since the ranks have a uniform distribution, the transformed ranks have a folded normal distribution. For details, see Nelson et al. (2005).
Use this method to compare group standard deviations (or variances) to the root mean square error (or mean square error). This method assumes that your data is approximately normally distributed. To use this method, each group must have at least four observations. For details about the ANOM for Variances test, see Wludyka and Nelson (1997) and Nelson et al. (2005). For an example, see Example of an Analysis of Means for Variances Chart.
This method provides a robust test that compares the group means of the absolute deviations from the median (ADM) to the overall mean ADM. Use ANOM for Variances with Levene (ADM) if you suspect that your data is nonnormal and cannot be transformed to normality. ANOM for Variances with Levene (ADM) is a nonparametric analog of the ANOM for Variances analysis. For details about the ANOM for Variances with Levene (ADM) test, see Levene (1960) or Brown and Forsythe (1974).
Note: ANOM for Ranges is only available for balanced designs and specific group sizes. See Restrictions for ANOM for Ranges Test.
Select an option from the most common alpha levels or specify any level with the Other selection. Changing the alpha level modifies the upper and lower decision limits.


(Only for ANOM for Variances) Changes the scale of the yaxis from standard deviations to variances.


