Provides a static picture of the location and spread of the Y variable (the process output). Each dot represents the actual location of a data point in the sample; however, if the sample is large, each dot can represent multiple points). If you also include a categorical x-variable, you can look at the location and spread of the Y at each level (for example, factor setting) of the x-variable.

Answers the questions:

- What is the general location of the Y data?
- How wide is the spread of the Y data?
- Are any unusual data points (outliers) present in the sample?
- If you change the level of an input variable (X), does it affect the location or spread of the output Y?

When to Use | Purpose |
---|---|

Mid-project | The first rule in data analysis is to always plot your data before running any statistical tests. The dotplot is a logical choice for any comparison tests in which you are looking at what happens to the process output under various conditions, such as changes to a process input. |

Mid-project | Assess if an input (X) has an impact on the process mean or process variation and help eliminate noncritical X's from consideration. |

Mid-project | Identify levels (settings) of the process input that have the desired impact on the output mean or variation. |

Mid-project | Communicate the effects of process inputs on the process output to project stakeholders. |

Numeric Y, with optional discrete X (categories for comparison).

There are two common data layouts you can use with dotplots:

- Choose Dotplot with groups (stacked data) when you enter one column for the y-variable and one for the x-, or categorical, variable (optional). Note: You can have up to four categorical variables. Minitab draws a separate dotplot for each combination of levels of the categorical variables, but the plots all appear in the same graph window. This arrangement is handy for making comparisons across levels of x-variables.
- Choose Dotplot with multiple Y's (unstacked data) when you enter the Y data into a separate column for each level of the x-variable. Minitab displays a dotplot for each Y. The plots can either be plotted in separate graph windows or in the same graph window with a common scale.

- You can use the dotplot with up to three nested x-variables. For example, you could plot sales by store, day of the week, and time of day.
- The dotplot does not provide statistical evaluation of possible outliers. In the case for which you have sufficient data (a sample size greater than 20), use the boxplot.
- The dotplot does not provide a good visual comparison when the number of levels of an x-variable are high. If the number of levels of an x-variable is greater than five, the boxplot provides a better visual comparison than the dotplot (assuming more than 20 points per category).