2 1 point A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet). The regression equation is Price (in thousands) 17.1 +0.0643 Size (sq. ft.) Predictor Coef Constant 17.06 SE Coef T 24.59 P 0.69 0.491 Size (sq. ft.) 0.06427 0.01224 5.25 0.000 5-48.5733 R-5q-37.5% R-Sqladj)-36.1% Predicted Values for New Observations Size (sq. ft.) Fit SE Fit 2000 145.61 7.07 95% CI (131.38, 159.83) 95% PI (46.80,244.41) Use the equation of the least squares line to predict the selling price of a home that is 1,742 square feet in size. $143,773 $299,000 $129,111 $201.873 $115,582 Previous Next * Data were collected on the age (in years), mileage (in thousands of miles), and price (in thousands of dollars) of a random sample of used Hyundai Elantras. Output is provided. The regression equation is Price 15.2-0.0101 Mileage-1.55 Age Predictor Constant Mileage Age S-1.39445 Coef 15.2174 SE Coef 0.6112 T P 24.90 0.000 -0.01005 0.01977 -1.5466 0.3508 -0.51 -4.41 0.616 0.000 R-Sq-89.0% R-Sq(adj)-88.0% One of the cars in the sample was a 5-year-old Hyundai Elantra with 87.1 (thousands) of miles being sold for $6,000. What is the predicted price of the car? $6,288 $6,570 $5,999 $6,999 $6,000 Previous Next 4 1 point A student working an independent research project wants to investigate if there is an association between the amount of sleep someone gets and their body mass index (BMI)-an Indicator of body fatness. For a sample of 45 students, she records their BMI and the average amount of sleep they get on weeknights over a two-week period. What would it mean for average amount of sleep to be negatively correlated with BMI? 0000 There is no association between the average amount of sleep and BMI. It would mean that individuals who tend to have lower BMIs get less sleep, It would mean that individuals who get more sleep tend to have lower BMIs Only positive association can occur between these two variables. It would mean that individuals who get less sleep tend to have lower BMIs. Previous Next 6 1 point Fast food restaurants are required to publish nutrition information about the foods they serve. Nutrition information about a random sample of 15 McDonald's lunch/dinner menu items (excluding sides and drinks) was obtained from their website. We wish to use the total fat content (in grams) to better understand the numbe of calories in the lunch/dinner menu items at McDonald's. Computer output is provided. The regression equation is Calories 137.1+15.06 Total Fat (g) Predictor Constant Coef 137.08 SE Coef T P 40.64 3.37 0.005 Total Fat (g) 15.055 1.649 9.13 0.000 S-62.7442 R-Sq-86.5% R-Sq(adj)-85.5% Predicted Values for New Observations Total Fat (g) Fit 25 SE Fit 95% CI 513.5 16.7 (477.4,549.5) 95% Pl (373.2,653.7) Interpret the slope in this regression model. We predict the number of calories to increase by 15.06 calories for each additional gram of fat in McDonald's lunch/dinner menu items. We predict the number of calories to increase by one for each additional 15.06 grams of fat in McDonald's lunch/dinner menu items. We predict the number of calories to increase by 137.1 calories for each additional gram of fat in McDonald's lunch/dinner menu items. We predict the amount of fat will increase by 15.06 grams for each additional one calorie in McDonald's lunch/dinner menu items. Previous Next 7 1 point For the relationship between Calories and Carbs, here is the equation of the line of best fit: Regression Equation: Calories 2.36+ 4.432 Carbs The range of Carb values in the dataset was between 17 and 47 Carbs. What would you say if asked to predict the number of Calories if a cereal had 60 Carbs? y hat-268.28 y hat-300.15 This is an extrapolation and it is dangerous to make a prediction. y hat 126.459 Previous