Chapter 15: Chi-Squares Flashcards
when are chi-square tests used?
when variables are categories or counts
when should the null not be rejected?
when the discrepancy between the observed and expected values is small
when should the null be rejected?
when the discrepancy between the observed and expected values is large
2 main characteristics of the chi-square distribution
- it’s positively skewed
- the minimum value is 0
goodness of fit test
Uses frequency data from a sample to test hypotheses about the shape or proportions of a population
observed frequencies
the data you collect
expected frequencies
computed by the proportions from the null
what is the most common null hypothesis
all proportions are equal
degrees of freedom for the goodness of fit test
df= c-1
expected frequencies formula
fe= pn
chi-square statistic formula
sum of (fo-fe)2/fe
chi-square test of independence
Compares the proportion of two variables
degrees of freedom for the test of independence
df= (number of rows -1) * (number of columns-1)
assumptions of a chi-square test
- observations are independent
- each cell should have an expected frequency greater than 5
effect size for chi-squares
use cohen’s w for goodness of fit and phi-coefficient for 2x2 tests of independence
