Utilizing the background materials present a research question and a null and alternative hypothesis that is consistent with Chi-square analysis.

References

• EZSPSS (2019). Easy SPSS Tutorial: Chi Square Test in SPSS, Including Interpretation. Retrieved fromhttps://www.youtube.com/watch?v=A_oV3MB53Y0(5:50)

• Lund Research. (2018). Chi-Square Test for Association using SPSS Statistics. Retrieved fromhttps://statistics.laerd.com/spss-tutorials/chi-square-test-for-association-using-spss-statistics.php

• Martin, G. (2019). Statistics made easy ! ! ! Learn about the t-test, the chi square test, the p value and more [Video File] Retrieved fromhttps://www.youtube.com/watch?v=I10q6fjPxJ0(12:49)

• Qi, Y., Wang, F., & Zhang, L. (2018). Limiting distributions of likelihood ratio test for independence of components for high-dimensional normal vectors.Annals of the Institute of Statistical Mathematics, 1-36.Retreived from ProQuest

• Walter, E. (2020). SPSS Chi Square [Video File]. Retrieved fromhttps://www.youtube.com/watch?v=Y0Oxi6zW-IE(6:04)

NOTES:

ONLY USE GROUPED VARIABLES FOR CHI SQUARE. When you propose your Chi Square hypotheses use 2 variables that are nominal variables, also known as categorical or grouped variables. Some examples might include gender (male and female groups), hair color (blonde, brown, black, red, other), business location (rural or urban location), location (Texas, California, or Alaska), voting preference (Red, Blue, or Independent), access to freeway (near-by, moderate distance, far away), membership (belongs to the Rotary Club, does not belong). You can use ordinal variables too. These are variables that are in some kind of order like rank (employee, supervisor, manager, director, exec), facility size (small, medium and large). Chi square tests of independence only work for these types of variables. You CANNOT use a numerical value as a variable in a Chi Square analysis.