Provides a summarize of univariate statistics and computes mean by groups based on categories.
The Descriptives procedure displays univariate summary statistics for several variables in a single table. Optionally, you can calculate subgroup means and related univariate statistics for dependent variables within categories of one or more independent variables.
Choose the columns you want to describe.
To select nonconsecutive columns, press and hold down CTRL, and then click each item.
You can select many columns. Use the Ctrl key to select (or unselect) distant columns.
•Grouping Variables (optional):
Enter the column containing the grouping variable to display descriptive statistics separately for each value of the specified variable.
The display of outputs of VisualStat.
The data columns must be numeric. The Descriptives procedure is very efficient for large files (thousands of cases). The optional grouping column can be numeric, text, or date-time. VisualStat automatically omits missing data from the calculations.
Displays a histogram, a histogram with a normal curve, and a boxplot.
Choose to display a histogram for each variable
•Histogram with Normal Curve:
Choose to display a histogram with a normal curve for each variable
•Boxplot of data:
Choose to display a boxplot for each variable
Choose the options you want.
oExclude missing values: Check to excludes rows that have missing values.
oInverted Bar: Check to reverse the axes.
Subjects were students in grades 4-6 from three school districts in Ingham and Clinton Counties, Michigan. Chase and Dummer stratified their sample, selecting students from urban, suburban, and rural school districts with approximately 1/3 of their sample coming from each district. Students indicated whether good grades, athletic ability, or popularity was most important to them. They also ranked four factors: grades, sports, looks, and money, in order of their importance for popularity. The questionnaire also asked for gender, grade level, and other demographic information.
You want to compare the age of boys and girls. You choose to display a boxplot of the data.
1.Open the DataBook summary.vstz
2.Select the sheet PopularKids
3.Choose the tab Statistics, the group Basic Statistics and the command Descriptives
4.In Variables, select Age
5.In Grouping Variables (optional), select Gender
6.Click Charts page and check Boxplot of data.
Report window output
Analysis Variable : Age
Gender N Mean Std Dev
boy 227 10.5286 1.0100
girl 251 10.3267 0.9407
<total> 478 10.4226 0.9784
Chart window output
The means shown in the Report window and the boxplots indicate that the boys are older than the girls and associated data have a smaller spread.