Analysis of Variance

A process of determining similarities between like groups. Analysis of variance is used in marketing to determine how likely groups with similar demographic backgrounds are to respond to a particular campaign.

Variance analysis is usually associated with explaining the difference (or variance) between actual costs and the standard costs allowed for the good output. For example, the difference in materials costs can be divided into a materials price variance and a materials usage variance. The difference between the actual direct labor costs and the standard direct labor costs can be divided into a rate variance and an efficiency variance. The difference in manufacturing overhead can be divided into spending, efficiency, and volume variances. Mix and yield variances can also be calculated.

Variance analysis helps management to understand the present costs and then to control future costs. Variance analysis is also used to explain the difference between the actual sales dollars and the budgeted sales dollars. Examples include sales price variance, sales quantity (or volume) variance, and sales mix variance. A difference in the relative proportion of sales can account for some of the difference in a company’s profits. The ANOVA test is the initial step in identifying factors that are influencing a given data set. After the ANOVA test is performed, the analyst is able to perform further analysis on the systematic factors that are statistically contributing to the data set’s variability. ANOVA test results can then be used in an F-test on the significance of the regression formula overall.

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