How to Analyze LIKERT SCALE ITEM with SPSS: Crosstabulation, Chi-Square, Cramer's V, Kendall's Tau-b

In this video we discuss the following:
The chi-square test of association is a statistical test used to determine if there is a significant association between two categorical variables. It involves calculating the chi-square statistic, which is a measure of how much the observed frequencies of the data deviate from the expected frequencies, assuming no association between the variables. If the calculated chi-square value is greater than a critical value based on the degrees of freedom and a chosen level of significance, we reject the null hypothesis of no association and conclude that there is a significant association between the two variables.

Cramer's V is a measure of association for categorical variables. It is based on the chi-square test statistic and ranges from 0 to 1. A value of 0 indicates no association, while a value of 1 indicates a perfect association. Cramer's V is calculated by taking the square root of the chi-square statistic divided by the total number of observations in the contingency table, multiplied by the minimum of the number of rows and the number of columns in the table, minus 1.

Kendall's Tau-b is another measure of association for categorical variables. It is a non-parametric statistic that measures the strength and direction of association between two ordinal variables. Kendall's Tau-b ranges from -1 to 1, with a value of 0 indicating no association, a value of 1 indicating a perfect positive association, and a value of -1 indicating a perfect negative association. Kendall's Tau-b is calculated by comparing the number of concordant and discordant pairs of observations in the data, adjusting for tied ranks, and dividing by the total number of pairs