Use factors during an experiment in order to determine their effect on the response variable. Factors can only assume a limited number of possible values, known as factor levels. Factors can be a categorical variable or based on a continuous variable but only use a few controlled values in the experiment.

For example, you are studying factors that could affect plastic strength during the manufacturing process. You decide to include Additive and Temperature in your experiment. The additive is a categorical variable. It can only be type A or type B. Conversely, temperature is a continuous variable, but here it is a factor because only three temperatures settings of 100C, 150C and 200C are tested in the experiment.

Factor | Additive | Temperature |
---|---|---|

Level | A | Low (100C) |

Level | B | Medium (150C) |

Level | High (200C) |

Minitab's make patterned data capability can be helpful when entering numeric factor levels. For example, to enter the level values for a three-way crossed design with a, b, and c (a, b, and c represent numbers) levels of factors A, B, C, and n observations per cell, Make Patterned Data 3 times, one time for each factor, as shown:

Dialog item | Factor A | Factor B | Factor C |
---|---|---|---|

From first value | 1 | 1 | 1 |

To last value | a | b | c |

Number of times to list each value | bcn | cn | n |

Number of times to list the sequence | 1 | a | ab |