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academics in their confidence that tenure rules are clear, with men feeling more confident. The 4500 faculty members in the survey were asked to evaluate

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academics in their confidence that tenure rules are clear, with men feeling more confident. The 4500 faculty members in the survey were asked to evaluate policies on a scale of 1 to 5 (very unclear to very clear). The mean response about the criteria for tenure was 3.51 for females and 3.55 for males, which was indicated to meet the test for statistical significance. Use this study to explain the distinction between statistical significance and practical (or economic) significance. In other words, even if a difference is statistically significant, is the magnitude of the difference important from a practical policy standpoint? (5 total points) (5) Anthropologists often try to reconstruct information using partial human remains at burial sites. For instance, after finding a femur (thighbone), they may want to predict how tall an individual was. An equation they use to do this y 61.4+2.4x , where yy is the predicted height and x is the length of the femur, both in centimeters. (5 points total) a) Identify the y-intercept and slope of the equation. Interpret the slope. (2.5 points) b) A femur found at a particular site has length of 50 cm. What is the predicted height of the person who had that femur? (2.5 points) (6) The variables y = annual income (thousands of dollars), *, = number of years of education, and *2 = number of years of experience in job are measured for all the employees having city-funded jobs, in Knoxville, Tennessee. The following prediction equations and correlations apply: i. y=10+1.0x, r = 0.30 ii. y=14+0.4x2 r = 0.60 The correlation is -0.40 between X, and X, . Which of the following statements are true? (5 points) a) The strongest sample association is between y and X2 . b) The weakest sample association is between *, and c) The prediction equation using *2 to predict *: has negative slope. ) A SD increase in education corresponds to a predicted increase of 0.3 SD in income. e) There is a 30% reduction in error in using education, instead of } , to predict income. f) Each additional year on the job corresponds to a $400 increase in predicted income. When *, is the predictor of y, the sum of squared residuals (SSE) is larger than when *2 is the predictor of y. h) The predicted mean income for employees having 20 years of experience is $4000 higher than the predicted mean income for employees having 10 years of experience. i) If s = 8 for the model using *, to predicty, then it is not unusual to observe an income of $70,000 for an employee who has 10 years of education. j) It is possible that S, = 12.0 and 5x1 = 3.6 k) It is possible that y = 20 and *1 =13

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