PSYC2010 Lecture Notes - Lecture 9: Statistical Hypothesis Testing, Standard Score, Covariance
Document Summary
Chi-square test of independence/contingency chi-square used to determine whether two categorical variables are related or are independent (e. g. gender and preferred car colour) Contingency tables the cells contain the observed frequencies of individuals in that particular sample and that particular category, it represents frequencies of joint occurrence. Chi-square test of independence two variables are considered to be independent when the frequency dist for one variable has the same shape for all levels of the second variable. If chi-square is not sig then the two variables are considered independent (e. g. salary is not dependent on gender), if chi-square is sig then the two variables are considered likely to be related (shapes of distributions differ) Goodness-of-fit does the observed data fit the model (one-way chi square) Independence/contingency - are the two variables independent (two way chi square), still asking if the data fits the model but the model is that the two variables are independent.
