This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.

The values in the response information table are for the response variable and do not depend on the validation method. The statistics take weights into account.

The number of non-missing values.

Percentage of the total number of observations in the training data set and the test data set.

A commonly used measure of the center of a batch of numbers. The mean is also called the average. It is the sum of all observations divided by the number of (nonmissing) observations.

If the data set contains
with mean , then the standard deviation of the sample is:

Term | Description |
---|---|

observation | |

mean of the observations | |

N | number of nonmissing observations |

The smallest value in the data set.

25% of your sample observations are less than or equal to the value of the
1^{st} quartile. Therefore, the 1^{st} quartile is also
referred to as the 25^{th} percentile.

The sample median is in the middle of the data: at least half the observations are less than or equal to it, and at least half are greater than or equal to it.

Suppose you have a data set that contains N values. To calculate the median, first order your data values from smallest to largest. If N is odd, the sample median is the value in the middle. If N is even, the sample median is the average of the two middle values.

75% of your sample observations are less than or equal to the value of the
third quartile. Therefore, the third quartile is also referred to as the
75^{th} percentile.

The largest value in the data set.