Use Individual Value Plot to assess and compare sample data distributions. An individual value plot shows a dot for the actual value of each observation in a group, making it easy to spot outliers and see distribution spread.
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.
The following individual value plot shows the diameters of plastic pipes that were measured during three weeks of production.
After you create the graph, you can add 95% confidence interval bars to create an interval plot. For more information, go Customize the individual value plot. Use an interval plot to assess and compare confidence intervals of the means of 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. Usually, the larger the sample size, the smaller and more precise the confidence interval.
The following plot shows the means and 95% mean confidence interval bars for the plastic pipe data that is shown in the previous individual value plot.
To create an individual value plot, choose , then select the option that matches your data. For more information, go to Choose an individual value plot.
If the sample is too large, the individual data points on the plot may be too densely packed together and the distribution may be difficult to assess. To assess the shape of a sample distribution with more than 50 observations, consider using Boxplot or Histogram instead.