0.2 Writing up chi-square

Writing up your chi-square

About the Authors

• John R. Slate is a Professor at Sam Houston State University where he teaches Basic and Advanced Statistics courses, as well as professional writing, to doctoral students in Educational Leadership and Counseling. His research interests lie in the use of educational databases, both state and national, to reform school practices. To date, he has chaired and/or served over 100 doctoral student dissertation committees. Recently, Dr. Slate created a website, Writing and Statistical Help to assist students and faculty with both statistical assistance and in editing/writing their dissertations/theses and manuscripts.
• Ana Rojas-LeBouef is a Literacy Specialist at the Reading Center at Sam Houston State University where she teaches developmental reading courses. She recently completed her doctoral degree in Reading, where she conducted a 16-year analysis of Texas statewide data regarding the achievement gap. Her research interests lie in examining the inequities in achievement among ethnic groups. Dr. Rojas-LeBouef also assists students and faculty in their writing and statistical needs on the Writing and Statistical website, Writing and Statistical Help

The following is an example of how to write up (in manuscript text) your Chi-Square statistics. This module is used with a larger Collection (Book) authored by John R. Slate and Ana Rojas-LeBouef from Sam Houston State University and available at: Calculating Basic Statistical Procedures in SPSS: A Self-Help and Practical Guide to Preparing Theses, Dissertations, and Manuscripts

Gender Differences in Reading Group Membership

Research question

The following research question was addressed in this investigation: What is the difference between boys and girls in their reading group membership?

Results

To ascertain whether a difference was present in reading group membership (i.e., Excellent, Good, Extremely Poor) between boys and girls, a Pearson chi-square was conducted. This statistical procedure was viewed as the optimal statistical procedure to use because frequency data were present for reading group membership and for gender. As such, chi-squares are the statistical procedure of choice when both variables are categorical. In addition, with the large sample size, the available sample size per cell was more than five. Therefore, the assumptions for utilizing a chi-square were met.

For this research question in which the focus was placed on reading group membership between boys and girls, the result was statistically significant, χ 2 (2) = 122.86, p <.001. The effect size for this finding, Cramer’s V , was moderate, .32 (Cohen, 1988). As can be seen in Table 1, 47.30% of the girls were in the Excellent Reader group, compared to only 21.4% of the boys. Most of the boys were in the Extremely Poor Reader group, 57.40%, compared to only 27.30% of the girls.

Reference

• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.) . Hillsdale, NJ: Lawrence Erlbaum.

Spss statistical output