- A test of independence may be appropriate if we are examining the relationship between two categorical variables in one population. For this situation what is the population? What is the explanatory variable? What is the response variable?
- What are the hypotheses for the Test of Independence? State hypotheses with reference to the context of the scenario.
- The spreadsheet of the data looked like this:
| Driver | Gender | Alcohol in last two hours? |
|---|---|---|
| Driver 1 | M | Yes |
| Driver 2 | F | No |
| Driver 3 | F | Yes |
| . . . |
. . . |
. . . |
| Driver 619 | M | No |
- We will not use the raw data. Instead we will use the summarized data shown in the table below.
| Drank alcohol in last 2 hours? | Yes | No | Totals |
|---|---|---|---|
| Male | 77 | 404 | 481 |
| Female | 16 | 122 | 138 |
| Totals | 93 | 526 | 619 |
- Use StatCrunch to find expected counts, the Chi-square test statistic and the P-value. (directions)
Copy and paste your StatCrunch table into the textbox.
- How many males in the sample are expected to answer yes to question about alcohol consumption in the last two hours? Show how to calculate this expected count and explain what it means relative to the hypotheses.
- Explain how we know that this data meets the conditions for use of a chi-square distribution .
- State a conclusion at a 5% level of significance. Do you think that the data supports the Oklahoma law that forbids sale of 3.2% beer to males and permits it to females?
