Category: Analysis of Variance (ANOVA)

Fisher’s 1-way ANOVA is a classic analysis of variance utilized in statistics to determine if there are statistical differences between the means of two or more unrelated groups.

ANOVA is a powerful statistical method for comparing several samples (3 or more) to each other to see if the populations that the means came from are statistically different.

Your data has failed the assumption of normality needed for a parametric test of hypotheses. If you have two or more groups you want to analyze, what do you do? Maybe the Mood’s Median Test will help. 

In many cases, you want to compare the means of samples. But, comparing variances can be just as important. The F test is the statistical tool you would use for that.  

If you are curious as to whether the means of greater than 2 groups are statistically different or not you could use a 1-way ANOVA. But, if you have multiple treatment groups and want to compare the means to a control group, then you can use Dunnett’s 1-way ANOVA.  ANOVA stands for Analysis of Variance. […]

In 1920, Sir Ronald A. Fisher invented a statistical way to compare data sets. Fisher called his method the analysis of variance, which was later dubbed an ANOVA. This method eventually evolved into Six Sigma data set comparisons. The F ratio is the probability information produced by an ANOVA. It was named for Fisher. The […]

The analysis of variance (ANOVA) procedure is conducted during the Analyze phase of a Six Sigma project. Assessing results from an ANOVA table can present a challenge making it difficult to understand precisely what conclusions to draw. However, there is an easy way for Master Black Belts to explain to their charges the ANOVA procedure. […]

Three methods used to dissolve a powder in water are compared by the time (in minutes) it takes until the powder is fully dissolved. The results are summarized in the following table: It is thought that the population means of the three methods m1, m2 and m3 are not all equal (i.e., at least one m […]

Much of the Six Sigma DMAIC methodology is concerned with finding differences: Do people do a certain job the same way or are there differences? Will a particular change make a difference in the output? Are there differences in where and when a problem occurs? In most cases, the answer to all these questions is […]