What are the estimated proportions? What are the null and alternative hypothesis? Chapter 7 (see section 7.7 “step 2” and table 7.17) has a rule of thumb for when we can do a specific test in this instance . Do we satisfy this rule of thumb? What will our test statistic be? Perform the test, what do you conclude?
A reason people give for drinking coffee is “alertness” or “energy”. This could be the case for kids who drink coffee. Or they could be groggier from a lack of sleep due to coffee. We asked n1=50 14-year-old kids who drink coffee if they “felt alert” x1=30 answered yes, we then asked n2=50 kids who don’t drink coffee and x2=20 of the kids answered that they the “felt alert”. We would like to compare these two proportions. .
- What are the estimated proportions?
- What are the null and alternative hypothesis?
- Chapter 7 (see section 7.7 “step 2” and table 7.17) has a rule of thumb for when we can do a specific test in this instance . Do we satisfy this rule of thumb? What will our test statistic be?
- Perform the test, what do you conclude?
Another way we could look at this would be to do a test of association on the 2x2 table constructed from this data (see the HIV IV drug example in the blackboard content directory for 04/06/22->additional information->OR RR and categorical-> Chi square
- Please construct the table (some blank 2x2s provided - please label as tables)
- What is the new null and alternative hypothesis?
- What are the expected counts (under the null hypothesis)
- What are the observed minus expected counts?
- What is the test statistic? How many degree of freedom?
- What do you conclude?
Yet two more ways we could look at this would be to look at the odds ratio or relative risks of these two groups and then perform an appropriate test on them (see chapter 3 and 7.7).
- What is the odds ratio in this case?
- What is the relative risk?
- What is the relative risk as a sentence in this case?
- What would our null and alternative hypothesis be if we were using odds ratios?
- What would the confidence interval for an odds ratio look like? (See section 6.6.3 and table 6-21).
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