If the response data are in separate columns for each factor level, the Residuals versus order and the Residuals versus the
variables plots are not available.
- Data plots
- Interval plot
- Use an interval plot to assess and compare the confidence intervals of the means of the groups. An interval plot shows a 95% confidence interval for the mean of each group. An interval plot works best when the sample size is at least 20 per group. Usually, the larger the sample size, the smaller and more precise the confidence interval.
- Individual value plot
- Use an individual value plot to assess and compare sample data distributions. An individual value plot works best when the sample size is less than 50. Like a boxplot, an individual value plot helps you to identify possible outliers and visualize distribution shape. However, unlike a boxplot, an individual value plot displays each value separately. Separate values are especially useful when you have relatively few observations or when it is important to assess the effect of each observation.
- Boxplot of data
- Use a boxplot to assess and compare the shape, central tendency, and variability of sample distributions and to look for outliers. A boxplot works best when the sample size is at least 20. If the sample size is less than 20, consider using an individual value plot instead.
- Residual Plots
- Use residual plots to examine whether your model meets the assumptions of the analysis. For more information, go to Residual plots in Minitab.
- Individual plots: Select the residual plots that you want to display.
- Display a histogram of the residuals.
- Normal probability plot of residuals
- Display a normal probability plot of the residuals.
- Residuals versus fits
- Display the residuals versus the fitted values.
- Residuals versus order
- Display the residuals versus the order of the data. The row number for each data point is shown on the x-axis.
- Four in one: Display all four residual plots together in one graph.
- Residuals versus the
- Enter one or more variables to plot versus the residuals. You can plot the following types of variables:
- Variables that are already in the current model, to look for curvature in the residuals.
- Important variables that are not in the current model, to determine whether they are related to the response.