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Cross Tabulation - Example

 

Data

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.

Source: http://lib.stat.cmu.edu/DASL/Datafiles/PopularKids.html

 

Analysis

  1. Open the DataBook PopularKid.vstz
    open this data file via the Help / Open Examples menu; it is in the Sample Data
  2. Choose the menu Analyze and the command CrossTabs, under group Data Summaries
  3. In Variables, select Gender, Grade and Urban/Rural
  4. Click OK

 

 

Output

By default, R code is printed after parsing and before evaluation.
You can avoid this in File / Option / Advanced menu.

DataSheet is converted to DataFrame, in the form DataBook.DataSheet

 

> .Table <- xtabs(formula = ~Gender+Grade+Urban.Rural, data = PopularKids.children)
> .Table
, , Urban.Rural = Rural

      Grade
Gender  4  5  6
  boy  16 24 26
  girl 28 29 26

, , Urban.Rural = Suburban

      Grade
Gender  4  5  6
  boy  14 29 46
  girl  8 17 37

, , Urban.Rural = Urban

      Grade
Gender  4  5  6
  boy  24 33 15
  girl 29 44 33


> remove(.Table)

 

 

Results

In this layout, VisualStat creates a two-way table for each level of the layering variable, Urban/Rural. The row variable is Gender and the column variable is Grade. It may be easier for you to compare your data in a different layout. You can change your table layout by designating variables to be across rows, down columns, or as layers.

 

Resource