Question 1 1 pts Scatterplot of Score on Final vs Score on Midterm 82 18 76 Score on Final 74 72 70 68 66 - 55 60 65 70 Score on Midterm Extra study sessions were offered to students after the midterm to help improve their understanding of statistics. Student scores on the midterm and the final exam were recorded. The scatterplot shows final test scores against the midterm test scores. Which of the following statements correctly interprets the scatterplot? O All students have shown significant improvements in the final exam scores as a result of the extra study sessions. O The extra study session further confuses students. All student scores decreased from midterm to final exam. The extra study sessions seemed to help students who scored below a 70 on the midterm more than students who scored above a 70. O The extra study sessions were of no help. Each student's final exam score was about the same as his or her score on the midterm.Question 2 1 pts A city collected data on total weights (in pounds) of discarded garbage and sizes of the corresponding households (#people) for 8 randomly selected households. A least-squares regression model was created and the output is shown above. Which of the following least- squares equations show the correct model to predict the weight of garbage given the number of people in a selected household? 0 Predicted garbage weight = 4.85 + 11.16(number of people) 0 Predicted garbage weight = 1.93 + 4.85lnumber of people) 0 Predicted garbage weight = 5.78 + 1.46lnumber of people) 0 Predicted garbage weight = 11.16 + 4.85(number of people) Question 3 1 pts SE T- P- Term Coef VIF Coef Value Value Constant 11.16 5.78 1.93 0.089 Household 4.85 1.46 3.32 0.011 1.00 A city collected data on total weights (in pounds) of discarded garbage and sizes of the corresponding households (#people) for 8 randomly selected households. A least-squares regression model was created and the output is shown above. Calculate the residual for the household with 6 people and garbage weight of 38.11 lbs. O 6.17 O -2.15 O -6.17 O 2.15Question 4 1 pts Scatterplot of K vs Number of At Bats 180 160 140- 120- 100 80 60 O 40 A 20 100 200 300 400 500 600 Number of At Bats The scatterplot above shows the number of at-bats vs. the number of strikeouts for 41 randomly selected MLB players in 2014. Which of the circled points would be considered a high-leverage point? OD O B OC OAQuestion 5 1 pts Fitted Line Plot log10(Weight)= 0.0900 + 0.02501 Length 0.098I959 lllh q qua\" u an 30 5'0 {0 170 no Length The scatterplot above shows the transformed data of the length (inches) and weight (lbs) of 15 bears that were captured in Smokey Mountain National Park and later released deeper in the park away from campers. The transformed regression model iS: Iog(predl'cted weight) = 0.6906 + 0.02507(Iength) Using this model, predict the weight of a bear measuring 65 inches in length. 0 203 lbs 0 2.32 lbs 0 178 lbs 0 209 lbs Question 6 1 pts From 2001 to 2009, the population of a city went from 100,000 to 205,000 people. The population by year is listed in the table below. Put the data in your calculator and calculate a Least Squares Regression Model to predict the population given the year. Population (in 1000's) 0 H O 00 O \\l 0 Predicted population = 79.96+13.63(year) 0 Predicted population = 82.16+14.37(year) 0 Predicted population = 48.37+12.17(year) 0 Predicted population = 91.34+11.28(year) Question 7 1 pts From 2001 to 2009, the population of a city went from 100,000 to 205,000 people. The population by year is listed in the table below. Put the data in your calculator and calculate a Least- Squares Regression Model to predict the population given the year. 01 oz 0- Which of the following is the residual plot for LSRL for these data and interprets the residual plot correctly? The pattern in the residual plot indicates the linear model may not be the most appropriate model for these data. C) The pattern in the residual plot indicates the linear model may not be the most appropriate model for these data. 0 The pattern in the residual plot indicates the linear model is the most appropriate model for these data