Help with questions 1-4. Thank you.

1. A real estate agent would like to predict the selling price of a single-family house by predicting the price (in $1000) based on the square footage (in 100 ft2 ). Predictor Coef Stdev t-ratio p Constant 18.3538 14.8077 1.239 0.237 footage 3.8785 0.7936 4.887 0.003 S=14.629 R-sq=64.8% a. What is the explanatory variable? b. What is the equation for the regression line? c. What is the correlation coefficient? What does it indicate about the data? d. What is the coefficient of determination? Interpret in terms of the problem. e. Interpret the slope. f. How much would I expect to pay for a house that has 1500 ft ? 2. Following are the mean heights of Kalama children: Age (months) 18 19 20 21 22 23 24 25 26 27 28 29 Height (cm) 76.1 77.0 78 .1 78.2 78 .8 79.7 79.9 81.1 81.2 81.8 82.8 83.5 a. Determine the regression line. y=. 635 x+64. 928 b. What is the coefficient of determination? Interpret in terms of the problem. c. Interpret the slope. For every month the child lives they grow. 63 5 cm d. Predict the height of a 32 month old child. 85. 248cm3. The following output data from MINITAB shows the number of teachers (in thousands) for each of the states plus the District of Columbia against the number of students (in thousands) enrolled in grades K-12. Predictor Coef Stdev t-ratio p Constant 4.486 2.025 2.22 0.031 Enroll 0.053401 0.001692 31.57 0.000 s=2.589 R-sq=81.5% a. What is the equation of the least squares line? Interpret the slope. b. Find the correlation coefficient and coefficient of determination. Interpret in the context of the problem. 35.7 c. Predict the number of teachers if the number of students in the state is 35,700. 4. In the National Hockey League a team is awarded two points in the standings for each victory and one point for each tie. The table presents data from the 1991-1992 NHL regular season. The table below shows the points for each time and the difference between the goals scored and the goals allowed. Team Points Difference Team Points Difference Boston 84 -5 NY Islanders 79 -8 Buffalo 74 -10 NY Rangers 103 69 Calgary 74 -9 Philadelphia 75 -21 Chicago 87 21 Quebec 52 -63 Detroit 98 64 St. Louis 83 13 Edmonton 82 -2 San Jose 39 -140 Hartford 65 -36 Toronto 67 -60 Los Angeles 84 -9 Vancouver 96 35 Minnesota 70 -32 Washington 98 55 New Jersey 87 30 Winnipeg 81 7 What is the least-squares regression line? b. What is the residual for Chicago? c. Sketch the residual plot. Explain what the residual plot indicates