Concept explainers
Do taller adults make more money? The authors of the paper “Stature and Status: Height, Ability, and Labor Market Outcomes” (Journal of Political Economics [2008]: 499–532) investigated the association between height and earnings. They used the simple linear regression model to describe the relationship between x = Height (in inches) and y = log(Weekly gross earnings in dollars) in a very large sample of men. The logarithm of weekly gross earnings was used because this transformation resulted in a relationship that was approximately linear.
The paper reported that the slope of the estimated regression line was b = 0.023 and the standard deviation of b was sb = 0.004. Carry out a hypothesis test to decide if there is convincing evidence of a useful linear relationship between height and the logarithm of weekly earnings. Assume that the basic assumptions of the simple linear regression model are reasonably met.
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Chapter 13 Solutions
Introduction To Statistics And Data Analysis
- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardThis problem is inspired by a study of the “gender gap” in earnings in topcorporate jobs [Bertrand and Hallock (2001)]. The study compares totalcompensation among top executives in a large set of U.S. public corporations in the 1990s. (Each year these publicly traded corporations must report total compensation levels for their top five executives.)a. Let Female be an indicator variable that is equal to 1 for females and 0for males. A regression of the logarithm of earnings onto Female yields "ln (Earnings)" = 6.48 - 0.44 Female, SER = 2.65. (0.01) (0.05)i. The estimated coefficient on Female is -0.44. Explain what thisvalue means.ii. The SER is 2.65. Explain what this value means.iii. Does this regression suggest that female top executives earn lessthan top male executives? Explain.iv. Does this regression suggest that there is gender discrimination?Explain. b. Two new variables, the market value of the firm (a measure of firmsize, in millions of…arrow_forwardThe November 24, 2001, issue of The Economist published economic data for 15 industrialized nations. Included were the percent changes in gross domestic product (GDP), industrial production (IP), consumer prices (CP), and producer prices (PP) from Fall 2000 to Fall 2001, and the unemployment rate in Fall 2001 (UNEMP). An economist wants to construct a model to predict GDP from the other variables. A fit of the model GDP = , + P,IP + 0,UNEMP + f,CP + P,PP + € yields the following output: The regression equation is GDP = 1.19 + 0.17 IP + 0.18 UNEMP + 0.18 CP – 0.18 PP Predictor Coef SE Coef тР Constant 1.18957 0.42180 2.82 0.018 IP 0.17326 0.041962 4.13 0.002 UNEMP 0.17918 0.045895 3.90 0.003 CP 0.17591 0.11365 1.55 0.153 PP -0.18393 0.068808 -2.67 0.023 Predict the percent change in GDP for a country with IP = 0.5, UNEMP = 5.7, CP = 3.0, and PP = 4.1. a. b. If two countries differ in unemployment rate by 1%, by how much would you predict their percent changes in GDP to differ, other…arrow_forward
- Anarrow_forwardThe rental of an apartment (?R) near campus is a function of the square footage (??Sq). A random sample of apartments near campus yielded the following summary statistics: ?¯R¯ = $340, ??¯Sq¯ = 93, ??sR = $ 29.1, and ???sSq= 10.5. Suppose also that the correlation between price and weight is ?r = 0.83. (a) Write the implied least squares linear regression equation. (b) Suppose an apartment has 75 sqft. Predict its price based on the above model. (c) Suppose the true rental of the apartment in part (b) is $ 345. What is the value of the residual?arrow_forwardZagat’s publishes restaurant ratings for various locations in the United States. The following table contains the Zagat rating for food, décor, service, and the cost per person for a sample of 100 restaurants located in New York City and in a suburb of New York City. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the ratings for food, décor, and service. Predict the mean cost per person for a restaurant with a sum-mated rating of 50. What should you tell the owner of a group of restaurants in this geographical area about the relationship between the summated rating and the cost of a meal? Location Food Décor Service Summated Rating Coded Location Cost Bins Midpoints City 22 14 19 55 0 33 19.99 25 City 20 15 20 55 0 26 29.99 35 City 23 19 21 63 0 43 39.99 45 City 19 18 18 55 0 32 49.99 55 City 24 16 18 58 0 44 59.99 65 City 22 22 21 65 0 44 69.99 75 City 22 20 20 62 0 50 79.99 85 City 20 19…arrow_forward
- Seven North American Green Frogs (Rana clamitans) had their jumping distance recorded (in mm) multiple times in a laboratory. The mean jumping distance for these frogs along with their length (measured from snout to vent in miMillimeters) are presented in the table below. Length of Frog 52 68 37 65 77 81 59 Mean Jumping Distance 546 673 415 659 793 814 563 (a) Determine the linear regression model that will best predit the mean jumping distance of a North American Green Frog based on the frog's length. (b) How well does the linear regression model fit this sample data? (c) Use the linear regression model to predict the mean jumping distance of a North American Green Frog that is 48 mm in length. No excel, please.arrow_forwardwo thousand (2,000) adults ages 50 to 80 years were recruited into a 10-year prospective cohort study which started in 1971. The purpose of the study was to examine the effect of gender on death at the end of the study (died during the study period vs survived), controlling for age, years if smoking, and occupation. What is the most appropriate statistical analysis you would conduct to answer the research question? A. Multiple linear regression B. Survival analysisC. Multiple logistic regression.D. All of the abovearrow_forwardA study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Number ofFacilities AverageDistance(miles) 9 1.66 11 1.13 16 0.83 21 0.61 27 0.51 30 0.46 2. .Does a simple linear regression model appear to be appropriate? Explain. a.No, the scatter diagram suggests that there is no relationship. b.No, the scatter diagram suggests that there is a curvilinear relationship. c.Yes, the scatter diagram suggests that there is a linear relationship. 3.Develop an estimated regression equation for the data corresponding to a second-order model with one predictor variable. (Round your numerical values to four decimal places.)arrow_forward
- What is the relationship between diamond price and carat size? 307 diamonds were sampled and a straight-line relationship was hypothesized between y = diamond price (in dollars) and x = size of the diamond (in carats). The simple linear regression for the analysis is shown below: Least Squares Linear Regression of PRICE Interpret the standard deviation of the regression model. a) We expect most of the sampled diamond prices to fall within $1117.56 of their least squares predicted values. b) We can explain 89.25% of the variation in the sampled diamond prices around their mean using the size of the diamond in a linear model. c) For every 1-carat increase in the size of a diamond, we estimate that the price of the diamond will increase by $1117.56. d) We expect most of the sampled diamond prices to fall within $2235.12 of their least squares predicted values.arrow_forwardThe National Survey of Drug Use and Health is a large annual cross-sectional survey of drug use in the United States. Using data from this survey, researchers wanted to assess the relationship between region in the country (Northeast, Midwest, South, and West) and past-month marijuana use among 18-25-year-olds. They obtained the following logistic regression model from the data: 1)What are the log odds of past-month marijuana use among 18-25-year-olds in the Midwest? 2)What is the probability of past-month marijuana use among 18-25-year-olds in the Northeast? 3)The odds of past-month marijuana use for 18-25-year-olds in the South is _______ times the odds of past-month marijuana use for 18-25-year-olds in the Northeast.arrow_forwardA researcher is using a panel data set on n = 1000 workers over T = 10 years (from 2001 through 2010) that contains the workers' earnings, gender, education, and age. The researcher is interested in the effect of education on earnings. Suppose you run a regression of earnings on person-specific and time-specific control variables. Can this regression be used to estimate the effect of gender on an individual's earnings or the effect of the national unemployment rate on an individual's earnings? A. Neither effect can be estimated using this regression. B. It can be used to estimate the effect of both gender and the national unemployment rate on an individual's earnings C. It can be used to estimate the effect of gender on an individual's earnings, but not the effect of the national unemployment rate on an individual's earnings. D. It can be used to estimate the effect of the national unemployment rate on an individual's earnings, but not the effect of gender on an individual's earnings.arrow_forward
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