Question: Using this data: Look at independent variables that are nominal/ordinal AND dependent variables that are nominal/ordinal. We'll be using the Chi-Squared Test. The Chi-Squared Test
Using this data:
Look at independent variables that are nominal/ordinal AND dependent variables that are nominal/ordinal.
We'll be using the Chi-Squared Test. The Chi-Squared Test tests whether two variables are independent of each other. In other words, we can tell if two variables are related or not.
Ho: gender is independent of whether someone believes it is a man's responsibility to take care of a woman.
Ha: gender is NOT independent of whether someone believes it is a man's responsibility to take care of a woman
Make a table that includes award counts for each category using data below:
Calculate "Expected Values". You will need to make an additional table for this on Excel.
Now fill in the Expected Values Table based on your calculations.
Now let's run the Chi-Squared Test.This test will produce a number that is compared to something called the p-value (significance level). The typical p-value is 0.05.
Conditions:
- Small p-values (<0.05) leads us to REJECT the null hypothesis.
- Large p-values (>0.05 leads us to RETAIN the null hypothesis.
Use the =CHISQ.TEST (or =CHITEST) command on Excel (remember the equal sign). For the Chi-square test, first highlight the observed range (all numbers except totalsin the observed values table), then expected range (all numbers except totals in the calculated expected values table). This produces the number you need.
Chi-squared test value=_________
Because _______________(number compared to p-value), we ____________________________________(hypothesis decision).
Therefore, based on the data, it seems that ___________________________________
_________________________________________________________________.
| Awards Yes | Awards No | Total | |
| Parental Education: MS | |||
| HS | |||
| AS | |||
| College | |||
| Grad | |||
| Total | GRAND TOTAL: 50 |
| male=0; female=1. |
| Masculine care: 1=strongly disagree; 2=disagree; 3=neutral; 4=agree; 5=strongly agree |
| gender | masc_care |
| 1 | 2 |
| 1 | 1 |
| 1 | 3 |
| 0 | 5 |
| 1 | 3 |
| 1 | 3 |
| 1 | 1 |
| 1 | 2 |
| 1 | 1 |
| 1 | 4 |
| 1 | 1 |
| 1 | 2 |
| 1 | 1 |
| 0 | 1 |
| 1 | 1 |
| 1 | 3 |
| 1 | 5 |
| 1 | 5 |
| 1 | 1 |
| 0 | 1 |
| 1 | 2 |
| 1 | 2 |
| 1 | 2 |
| 1 | 4 |
| 1 | 5 |
| 0 | 2 |
| 1 | 3 |
| 1 | 5 |
| 1 | 5 |
| 1 | 2 |
| 1 | 2 |
| 1 | 2 |
| 1 | 5 |
| 1 | 5 |
| 1 | 5 |
| 1 | 2 |
| 1 | 1 |
| 0 | 4 |
| 1 | 4 |
| 1 | 4 |
| 1 | 4 |
| 1 | 4 |
| 1 | 3 |
| 1 | 3 |
| 1 | 3 |
| 1 | 5 |
| 1 | 4 |
| 1 | 4 |
| 1 | 4 |
| 1 | 2 |
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