Class Notes (838,386)
Sociology (717)
SOC 280 (11)
Lecture 12

# Lecture 12 – Chi-square - summary page2.docx

4 Pages
116 Views

School
Department
Sociology
Course
SOC 280
Professor
Owen Gallupe
Semester
Winter

Description
1 Lecture 12 – Chi-square – summary page - ie male/female white/block/asian -chi-square tests tell you whether differences across categorical variables are significant or not. -compares the frequencies you actually find by the frequencies you would expect to get by chance. -Assumptions • Only time we don’t need to worry about normality and homogeneity of variance o Not based on normal curve which is why -independence of cases -expected cell counts are sufficient (no more than 20% of cells should have expected counts less than 5; none should have expected counts less than 1). If any are less than 5, that’s a problem. - makes the estimates unreliable if 20% is less than 5. If you don’t have enough cases with results you can trust its prone to random fluxuation and we run into issues. Example: Sex by contact with courts. Male Female Total Finish HS N expected N expected A Did not Finish HS N expected N Expected Total C B To get sell count: • Expected cell count = (row total/n) x (column total/n) x number of cases. • = (A/B) + (C/B) x B • To check expected cell counts: -“Analyse”“Descriptive Statistics””Crosstabs” -enter dependent variable into “Row” and independent variable into “Column” -under “Cells”, check “Expected” To get Chi-Square value need to calculate degrees of freedom as well • Degrees of freedom = (# of rows-1)x(# of columns -1) • Spss does this for
More Less

Related notes for SOC 280
Me

OR

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Join to view

OR

By registering, I agree to the Terms and Privacy Policies
Just a few more details

So we can recommend you notes for your school.