Skip to content(MATH 533 Week 7 Quiz)
- Question: Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Using data for n = 200 samples, the results below were … Complete parts a through d.
- Question: Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Use the β estimates to predict the number of runs scored by a team with 282 walks, 966 singles, 219 doubles, 15 triples, and 160 home runs.
- Question: Suppose you fit the first-order multiple regression model y = β0 + β1x1 + β2x2 + Ԑ to n = 25 data points and obtain the prediction equation ŷ = 31.26 + 1.59x1 + 2.48x2. The estimated standard deviations of the sampling distributions of β1 and β2 are 0.32 and 0.32 respectively.
- Question: The equation used to predict the total body weight (in pounds) of a female athlete at a certain school is ŷ = – 127 + 4.03x1 + 1.38x2, where x1 is the female athlete’s height (in inches) and x2 is the female athlete’s percent body fat, measured as x2%. Use the multiple regression equation to predict the total body weight for a female athlete who is 65 inches tall and has 18% body fat.
- Question: Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Using data for n = 200 samples, the results below were obtained. Complete parts a through d.
- Question: Data were gathered from a simple random sample of cities. The variables are Violent Crime (crimes per 100,000 population), Police Officer Wage (mean $/hr), and Graduation Rage (%). Using the accompanying regression table to answer the following questions consider the coefficient of Graduation Rate. Complete parts a through e.
- Question: Researchers developed a safety performance function (SPF), which estimates the probability of occurrence of a crash for a given segment of roadway. Using data on over 100 segments of roadway, they fit the model E(y) = β0 + β1x1 + β2x2, where y = number of crashes per three years, x1 = roadway length (miles), and x2 average annual daily traffic. (number of vehicles) = AADT.
- Question 12.3.4.T: Suppose you fit the first-order multiple regression model y = β0 + β1x1 + β2x2 + Ԑ to n = 25 data points and obtain the prediction equation ŷ = -50.11 + 5.44x1 + 1.33x2. The estimated standard deviations of the sampling distributions of β1 and β2 are 0.98 and 0.25 respectively.
- Question 12.3.13: Researchers developed a safety performance function (SPF), which estimates the probability of occurrence of a crash for a given segment of roadway. Using data on over 100 segments of roadway, they fit the model E(y) = β0 + β1x1 + β2x2, where y = number of crashes per three years, x1 = roadway length (miles), and x2 average annual daily traffic. (number of vehicles) = AADT.
- Question 9.4.3: The equation used to predict the total body weight (in pounds) of a female athlete at a certain school is ŷ = -113 + 3.34x1 + 1.05x2, where x1 female athlete’s height (in inches) and x2 is the female athlete’s percent body fat, … as x2%. Use the multiple regression equation to predict the total body weight for a female athlete who is 64 inches tall and has 30% body fat.
- Question 12.4.26: Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Use the β estimates to predict the number of runs scored by a team with 286 walks, 865 singles, 172 doubles, 32 triples, and 138 home runs.
- Question Section 15.4 Exercise 8: Data were … from a simple random sample of cities. The variables are Violent Crime (crimes per 100,000 population), Police Officer Wage (mean $/hr), and Graduation Rage (%). Using the accompanying regression table to answer the following questions consider the coefficient of Graduation Rate. Complete parts a through e.
