Provides a graphical means for assessing and communicating the relationship between two (or possibly three) variables.

Answers the questions:

- What is the nature of the relationship between two variables (usually a process output Y and a process input X; could also be two process inputs)?
- Is the relationship between the process output Y and a process input X the same for different levels (settings) of a second process input?

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

Start of project | Assists in developing alternatives measurement systems in cases where a variable is difficult or expensive to measure - you can use highly correlated and logically linked alternative variables as substitute variables. |

Mid-project | The first rule of data analysis is to graph the data before running any statistical tests. Use scatterplots along with any statistical tool that tests for relationships between variables, such as regression. |

Mid-project | Assess if an input (X) has a strong relationship with an output (Y) to help eliminate noncritical X's from consideration. |

Mid-project | Evaluate two inputs to eliminate inputs that duplicate the same information (for example, inputs of Degree Obtained and Years of School are likely to explain the same variation of the output). This case is common in multiple regression with many variables. |

End of project | If used earlier as part of the validation of the measurement system, it should be reapplied to the improved process to again validate the measurement system. |

Two numeric variables (both can be continuous or discrete), with optional categorical variables.

- Enter each variable into a single column.
- Place optional categorical variables in additional columns. You can use these variables to change visual aspects of the plot (for example, symbol types or colors) based on the value of the categorical variable.

- You can use categorical (grouping) variables with scatterplots to show the effects of different levels of a factor. For example, if you are plotting yield (Y) versus temperature (X), you could use different catalysts as a group variable (factor) and see whether the correlation between yield and temperature is the same or different for the different levels of catalyst.
- Minitab usually allows up to three categorical (grouping) variables for most plot characteristics.