Using Chi | pearson chi-square test
TheChiSquarestatisticiscommonlyusedfortestingrelationshipsbetweencategoricalvariables. ThenullhypothesisoftheChi-Squaretestisthatnorelationshipexistsonthecategoricalvariablesinthepopulation;theyareindependent. AnexampleresearchquestionthatcouldbeansweredusingaChi-Squareanalysiswouldbe:Isthereasignificantrelationshipbetweenvoterintentandpoliticalpartymembership?HowdoestheChi-Squarestatisticwork?TheChi-SquarestatisticismostcommonlyusedtoevaluateTestsofIndependencewhenusingacrosstabulation(also...
The Chi Square statistic is commonly used for testing relationships between categorical variables. The null hypothesis of the Chi-Square test is that no relationship exists on the categorical variables in the population; they are independent. An example research question that could be answered using a Chi-Square analysis would be:
Is there a significant relationship between voter intent and political party membership?
How does the Chi-Square statistic work?
The Chi-Square statistic is most commonly used to evaluate Tests of Independence when using a crosstabulation (also known as a bivariate table). Crosstabulation presents the distributions of two categorical variables simultaneously, with the intersections of the categories of the variables appearing in the cells of the table. The Test of Independence assesses whether an association exists between the two variables by comparing the observed pattern of responses in the cells to the pattern that would be ...