Which statistical test woul you use to assess whether or not there is a relationship between the variables SEX and HOURLY WAGES?
To assess whether there is a relationship between the variables SEX and HOURLY WAGES, you would typically use a statistical test called the chi-square test of independence.
Here's how you can perform this test:
1. Start by organizing your data into a contingency table. The rows represent the different categories of one variable (in this case, SEX - male and female), and the columns represent the different categories of the other variable (in this case, HOURLY WAGES - e.g., low, medium, high).
2. Calculate the expected frequencies for each cell in the contingency table. This can be done by multiplying the row total by the column total and dividing by the grand total.
3. Once you have your contingency table with observed and expected frequencies, you can calculate the chi-square statistic. This is done by summing up the squared difference between the observed and expected frequencies, divided by the expected frequencies.
4. Determine the degrees of freedom for the test. In this case, it is calculated as (number of rows - 1) multiplied by (number of columns - 1).
5. Look up the critical value for the desired level of significance (typically 0.05) and degrees of freedom in a chi-square distribution table. If the calculated chi-square statistic is greater than the critical value, you can reject the null hypothesis and conclude that there is a relationship between the variables SEX and HOURLY WAGES.
Keep in mind that the chi-square test assesses the independence between variables, not the strength or direction of the relationship. If you want to measure the strength and direction, you might consider other statistical methods such as regression analysis.