S Use S to assess how well the model describes the response. To determine how well the model fits your data, examine the goodness-of-fit statistics in the model summary table. The interval plot for differences of means displays the same information.Ĭonfidence intervals that do not contain zero indicate a mean difference that is statistically significant. The table displays a set of confidence intervals for the difference between pairs of means. Use the confidence intervals to determine likely ranges for the differences and to determine whether the differences are practically significant. Groups that do not share a letter are significantly different. Use the grouping information table to quickly determine whether the mean difference between any pair of groups is statistically significant. Use the grouping information table and tests for differences of means to determine whether the mean difference between specific pairs of groups are statistically significant and to estimate by how much they are different.įor more information on comparison methods, go to Using multiple comparisons to assess differences in group means. If your one-way ANOVA p-value is less than your significance level, you know that some of the group means are different, but not which pairs of groups.
![one way anova minitab one way anova minitab](https://i.ytimg.com/vi/pP3TAVfx9Po/maxresdefault.jpg)
For more information, go to Increase the power of a hypothesis test.
![one way anova minitab one way anova minitab](https://lsc.studysixsigma.com/wp-content/uploads/sites/6/2016/01/99344.png)
Verify that your test has enough power to detect a difference that is practically significant. P-value > α: The differences between the means are not statistically significant If the p-value is greater than the significance level, you do not have enough evidence to reject the null hypothesis that the population means are all equal. For more information, go to Statistical and practical significance. Use your specialized knowledge to determine whether the differences are practically significant. P-value ≤ α: The differences between some of the means are statistically significant If the p-value is less than or equal to the significance level, you reject the null hypothesis and conclude that not all of population means are equal. A significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. Usually, a significance level (denoted as α or alpha) of 0.05 works well. The null hypothesis states that the population means are all equal.
![one way anova minitab one way anova minitab](https://image.slidesharecdn.com/6906891/95/ng-bb-34-analysis-of-variance-anova-32-728.jpg)
To determine whether any of the differences between the means are statistically significant, compare the p-value to your significance level to assess the null hypothesis.