The purpose of this discussion is to allow you to consider how nonparametric tests are used and how two types of chi-square tests compare. To do this, you will need to explain statistical concepts and assess assumptions, limitations, and implications associated with statistical tests.
For your initial post,
- Describe the chi-square goodness-of-fit test. Explain what this test measures.
- Explain how the chi-square goodness-of-fit test is similar to and different from a simple frequency distribution.
- Describe the chi-square test of independence. Explain what this test measures and how it is similar to and different from the chi-square goodness-of-fit test.
- How do you know when to use one analysis over the other?
- Provide a real-world example in which either a goodness-of-fit test or a test of independence should be used.
Requirements: 500 words
Please make a referece to this chapter
The chi-square test of independence is used to determine the relationship between two variables. Therefore, it is used when we have an idea that the two variables are not connected. The test helps us decide whether our assumptions are plausible (Nominal Data and the Chi-Square Tests. P, 11). For example, when one wants to determine the relationship between education level and marital status within a particular ethnic group. We will collect data based on divorcee and their levels of education, while on the other hand, we will have the number of married couples and their education level. Based on our data, we will check how many divorced people have a degree and how many married couples have a degree. Based on the results, it is possible to determine whether the level of education is related to marital status.
On the contrary, the chi-square goodness-of-fit test determines whether the expected results are similar to the outcomes. Therefore, it is used to determine if the results are identical or not (Nominal Data and the Chi-Square Tests. P, 3).