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Unformatted text preview: STA 3024 Exam 1 Sample Questions In this file, the questions are sorted by chapter. On the actual exam, the questions from the two chapters will be mixed together. Also, please note that even though there are many more questions in this list from Chapter 3 than from Chapter 4, this does not reflect the proportion of questions from each chapter that will appear on the actual exam. Anywhere from 2540% of the questions on the exam will cover Chapter 4. Chapter 3: Contingency Tables 1. A researcher is conducting a chi-squared test with = 0 . 05 to see if happiness (not happy, pretty happy, or very happy) depends on level of income (low, medium, or high). She surveys a random sample of 2859 people, creates a 3 3 contingency table, and calculates a test statistic value of X 2 = 61 . 2. (Assume she has done everything correctly up to this point.) She then compares her observed test statistic value to a chi-squared distribution with df = 4, and she determines that her p-value is smaller than 0.001. Since her p-value is extremely small, she concludes that there is a strong association between income and happiness. How did she make a mistake? (A) She should have used a smaller df when calculating the p-value. (B) She should have used a larger df when calculating the p-value. (C) She cannot necessarily conclude that the p-value is smaller than 0.001. (D) She cannot necessarily conclude that there is a strong association. (E) She did not make a mistake. 2. A gas station offers three grades of gasoline: regular, plus, and premium. Plus is better than regular, and premium is better than plus. As defined here, grade of gasoline is (A) a nominal variable. (B) an ordinal variable. 3. Contingency tables are used when (A) both the explanatory and response variables are quantitative. (B) the response variable is quantitative, but the explanatory variable is categorical. (C) both the explanatory and response variables are categorical. (D) the response variable is categorical, but the explanatory variable is quantitative. 4. When analyzing the strength of an association, which of the following values for the differ- ence between proportions represents the same strength of association as a difference between proportions of- . 40? (A)- 2 . 50 (B)- . 40 (C)- . 60 (D)- 1 . 40 (E) none of the above 5. In a chi-squared test for a contingency table with three rows and two columns, a test statistic value of X 2 = 9 . 67 corresponds to a p-value (A) smaller than 0.001. (B) between 0.001 and 0.005. (C) between 0.005 and 0.010. (D) between 0.010 and 0.025. (E) between 0.025 and 0.050. 6. In a chi-squared test, if df = 3, then a test statistic value of X 2 = 20 . 95 corresponds to a p-value (A) smaller than 0.001....
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- Spring '08