The Importance of Fisher’s (1-way ANOVA) in Statistical Analysis

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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.

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How To Compare Data Sets – ANOVA

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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 […]

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Help for Practitioners Trying to Understand ANOVA Table

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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. […]

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Using ANOVA to Find Differences in Population Means

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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 […]

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When Does a Difference Matter? Using ANOVA to Tell

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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 […]

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