As mentioned earlier, the default statistic for analysis variables is SUM. There may be some instances, however, in which you want to display other statistics in your reports. To do so, you merely specify your desired statistic as an attribute in the DEFINE statement. Here's a list of the statistics you can request:

Statistic | Description |
---|---|

CSS | corrected sum of squares |

USS | uncorrected sum of squares |

CV | coefficient of variation |

MAX | maximum value |

MEAN | average value |

MIN | minimum value |

N | number of observations with nonmissing values |

NMISS | number of observations with missing values |

RANGE | range of values |

STD | standard deviation |

STDERR | standard error of the mean |

SUM | sum of the values |

SUMWGT | sum of the weight variable values |

PCTN | percentage of cell or row frequency to total frequency |

PCTSUM | percentage of cell or row sum to total sum |

VAR | variance of the values |

T | student's |

PRT | probability of a greater absolute value of student's |

Let's take a look at an example in which the mean statistic is requested.

##
Example 10.15
Section* *

The following REPORT procedure creates a report in which the average par and average yardage are reported for each of the four types of golf courses:

```
PROC REPORT data = stat480.penngolf NOWINDOWS HEADLINE;
title 'Average Size of Some PA Golf Courses by Type';
column Type Par Yards;
define Type / group 'Type of/Course' spacing = 6
width = 8;
define Par / mean format= 4.1
'Average/Par' width = 7 center;
define Yards / mean format = comma6.0 'Average/Yardage'
width = 7 spacing = 4 center;
RUN;
```

Type of Course | Average Par | Average Yardage |
---|---|---|

Private | 71.3 | 6,553 |

Public | 72.0 | 6,525 |

Resort | 72.0 | 7,071 |

SemiPri | 70.6 | 6,395 |

The COLUMN statement tells SAS that we only want to display three columns, namely `Type`, `Par`, and `Yards`, in that order. The first DEFINE statement tells SAS to use `Type` as a group variable, as well as specifies the column heading, spacing, and width. The **mean** that is present in the second DEFINE statement tells SAS to calculate the average `Par` for each `Type` of golf course. The second DEFINE statement also tells SAS how to format the result, as well as how to label, justify, and set the width of the `Par` column. The mean that is present in the third DEFINE statement tells SAS to calculate the average `Yards` for each `Type` of golf course. The third DEFINE statement also tells SAS how to format the result, as well as how to label, justify, and set the width and spacing of the `Yards` column.

Now, launch and run * * the SAS program, and review the output to convince yourself that SAS collapses the observations, and in so doing, calculates the averages of the

`Par`and

`Yards`variables for each

`Type`of golf course.

##
Example 10.16
Section* *

The following example illustrates the type of one-line report you get when the columns of your report contain only (numeric) analysis variables:

```
PROC REPORT data = stat480.penngolf NOWINDOWS HEADLINE;
title 'Size of Some PA Golf Courses';
column Par Yards;
define Par / mean format= 4.1
'Average/Par' width = 7 center;
define Yards / format = comma7.0 'Total/Yardage'
width = 7 spacing = 4 center;
RUN;
```

Average Par | Total Yardage |
---|---|

71.2 | 72,300 |

First, note that the COLUMN statement contains just two variables, `Par` and `Yards`, and that both are numeric variables. The first DEFINE statement tells SAS to calculate the average `Par`, as well as how to format the result and label, justify, and set the width of the column. The second DEFINE statement tells SAS to calculate the total yards, as well as how to format the result and label, justify, and set the width and spacing of the column.

Now, launch and run * * the SAS program, and review the output to convince yourself that SAS collapses all of the observations, and in so doing, calculates the average

`Par`and the total

`Yards`of all of the golf courses. It is in this way that we end up with just a one-line report.