Statistics – Spring 2008
Lab #10 – Chi-Square
Defined: Frequencies or proportions amongst levels of variables.
Variables: IV is categorical, DV is categorical
Relationship: Relationship between two or more variables.
Example: How do males/females vote guilty or not guilty?
Assumptions: Typically you want greater than 5 per cell.
; The first step of any statistical analysis is to first graphically plot the data.
; Graphs are produced within the output for “Crosstabs”, so see the section below for how to produce plots.
; There are no real assumptions for Chi-Square because you can’t have the typical type of assumptions (e.g.,
normality, linearity, homogeneity) when your data are categorical.
; Let’s look at the relationship between males/females and a few of the other categorical variables from our
; How to conduct Chi-Square
1. Select Analyze --> Descriptive Statistics --> Crosstabs
2. Move “sex” into “Rows” and “victimcrime” into “Columns”
FYI – it doesn’t matter which variable goes in which box, and you can do both plots if you want to.
3. Click “Statistics” and click “Chi-Square” and “Phi and Cramer’s V”.
4. Click “Display Clustered bar charts”
5. Click OK.
; The output is in three parts.
; Part 1 is the descriptive statistics. The descriptive statistics tell you the total number of cases, and the number
of cases within each cell. In this case, notice how many more females are participants in the study compared to
males. The second box below is called a “crosstabulation” box.
; Part 2 is the significance and effect size. The Pearson Chi-Square indicates that there is a significant
relationship between the two variables (sex and victimcrime). The second box is the strength of that
relationship. Use “Phi” when you have two variables, each with two levels (2 x 2). Use “Cramer’s V” for all