Statistics Exercise II: Statistical inference, 1- and 2-sample t-tests
These weekly exercises provide an opportunity for you to understand and apply statistical methods and analysis. Unless otherwise stated, use 5% (.05) as your alpha level (the cutoff for statistical significance).
#1. Define “power” in relation to hypothesis testing.
#2. Alpha (a) is used to measure the error for decisions concerning true null hypotheses. What is the beta (ß) error used to measure?
#3. In the following studies, state whether you would use a one-sample t-test or a two-independent-sample t-test.
Use SPSS and the data file found in syllabus resources (DATA540.SAV) to answer the following questions. Round your answers to the nearest dollar, percentage point, or whole number.
#4. Test the age of the participants (AGE1) against the null hypothesis H0 = 34. Use a one-sample t-test. How would you report the results?
a. t = -1.862, df = 399, p > .05 b. t = -1.862, df = 399, p < .05 c. t = 1.645, df = 399, p > .05 d. t = 1.645, df = 399, p
#5. What is the mean and standard deviation for the Lifestyle score (L)?
a. 31.22, 7.99 b. 36.19, 8.54 c. 30.03, 7.28 d. 55, 13
#6. The first case shown in the data file is a firefighter with a financial Risk-Taking score (R) of 38. What is his Risk-Taking z-score (hint: you will need to find the Risk-Taking mean and standard deviation)?
a. 0.179 b. -0.223 c. 1.342 d. -1.223
#7. Perform independent sample t-tests on the Lifestyle, Dependency, and Risk-Taking scores (L, D, and R) comparing men and women (GENDER1). Use p < .05 as your alpha level and apply a two-tailed test. On each of the three scales, do men or women have a significantly higher score?
a. Lifestyle: Men, Dependency: Women, Risk-Taking: Men.b. Lifestyle: Not significantly different, Dependency: Women, Risk-Taking: Men c. Lifestyle: Women, Dependency: Women, Risk-Taking: Mend. Lifestyle: Men, Dependency: Men, Risk-Taking: Not significantly different
#8. The median US salary is $50,700, according to US Census data. Using a one-sample t-test, test to see if participant income (INC1) is different from the national average. Use a two-tailed test and an alpha level of 5%.
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