A School 2 Duke 3 Michigan State 4 Marquette 5 Kentucky 6 Syracuse 7 Arkansas 8 Connecticut 9 Texas 10 Texas A&M 11 North Carolina 12 Florida 13 lowa 14 Tennessee 15 Memphis 16 Kansas 17 Oklahoma 18 Ohio State 19 Arizona 20 Indiana 21 Wisconsin 22 Alabama 23 UCLA 24 Washington 25 Illinois 26 Pittsburgh 27 California 28 West Virginia 29 Florida State 30 San Diego State 31 Villanova 32 Boston College 33 North Carolina State 34 LSU 35 UAB 36 Wichita State 37 Nevada Data B E Salary Expenses Revenues Winning% 1.40 7.40 12.40 90.00 1.60 6.30 11.00 67.74 1.10 5.80 5.80 66 67 1.90 5.60 12.90 64.52 0 38 5.60 12.40 65.63 0.80 5.60 11.10 72.41 1.50 5.50 7.90 90.00 1.30 5.10 12.00 83.33 0.63 4.90 6.50 74.07 1.40 4.80 15 00 77.78 1.70 4.60 6.50 80.00 0.80 4.50 10.50 73.33 0.80 4.50 5.40 77.78 1.20 4.50 5.60 90.32 1.00 4.30 11.80 75.86 1.00 4.10 6.20 74.07 0.83 4.10 11.40 85.19 0.70 4.10 16.60 63.33 0.78 3.80 11.90 62.96 0.70 3.80 12.00 65.52 1.00 3.70 6.50 60.72 0.91 3.70 7.10 80.65 0.89 3.20 5.00 82.76 0.70 3.20 11.30 83.33 0.49 3.20 7.80 79.31 0.85 3.10 6.00 67.86 0.70 3.10 4.90 66 67 0.74 2.90 6.80 67.86 0.36 2.60 73,33 0.51 2.60 4.20 89 29 0.53 2.50 340 80.00 0.90 2.40 11.40 72.41 0.72 2 20 4.60 75.86 0.60 2.10 1.90 82.14 0.41 2.00 75.00 0.26 1.70 3.30 83.33 2.60 3.10 22 Alabama 23 UCLA 24 Washington 25 Illinois 26 Pittsburgh 27 California 28 West Virginia 29 Florida State 30 San Diego State 31 Villanova 32 Boston College 33 North Carolina State 34 LSU 35 UAB 36 Wichita State 37 Nevada 38 Gonzaga 39 Southern Illinois 40 Northern Iowa 41 Montana 42 Delaware State 43 UNC Wilmington 44 Albany 45 Winthrop 46 Northwestern State B 1.00 0.91 0.89 0.70 0.49 0.85 0.70 0.74 0.36 0.51 0.53 0.90 0.72 0.60 0.41 0.26 0.50 0.21 0.18 0.12 0.19 0.17 0.11 0.20 0.76 C 3.70 3.70 3.20 3.20 3.20 3.10 3.10 2.90 2.60 2.60 2.50 2.40 2.20 2.10 2.00 1.70 1.60 1.30 1.20 1.10 0.91 0.90 0.78 0.74 0.47 D 6.50 7.10 5.00 11.30 7.80 6.00 4.90 6.80 2.60 4.20 3.40 11.40 4.60 1.90 3.10 3.30 2.50 1.20 1.20 1.30 0.91 0.44 0.16 0.52 0.35 60.72 80.65 82.76 83.33 79.31 67.86 66.67 67.86 73.33 89.29 80.00 72.41 75.86 82.14 75.00 83.33 90.00 68.75 71.88 79.31 61.29 78.13 66.67 76.67 77.42 07 Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. How many observations are there in this dataset? Question 2 5 pts Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. What is the equation of the line that the regression analysis produced (write y = Bo + B12, filling in the correct values for the betas) Remember, Bois the intercept coefficient and B, is the coefficient associated with your independent variable. Winning% = 76.86 0.22* Revenues Revenues - 76.86 -0.22* Winning% Winning%--0.22 + 76.86 Revenues Winning% - 76.86 +0.22 Revenues Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. In, this model, is revenue statistically significant? No Yes o o Question 4 2 pt When the confidence limits for slope coefficient are either both positive, or both negative, the slope coefficient must be significantly different from zero. True False In a simple regression model, there is one y-intercept because there is only one independent variable. In multiple regression, there is a y-intercept for each independent variable. True False Question 6 3 pts Is the relationship between Quantity and Price Positive or Negative in the provided data? Negative Positive Run the regression with Price as X variable and Quantity as Y variable. What is the adjusted R-squared in the given data set? Round it to three digits after decimal. Question 8 5 pts Run the regression with Price as X variable and Quantity as Y variable. Using the regression model you make, calculate the predicted Quantity, if price is $6. Round your answer to closest integer. B Income 1 2 3 A Quantity 19 16.0 24 29.3 4 27 13.5 5 30 21.3 6 24 29.1 7 34 27.5 16.2 8 8 39 9 41 27.8 20 14.0 39 Price $ 12.66 $ 7.61 $ 11.08 $ 7.84 $ 8.65 $ 6.32 $ 7.04 $ 8.45 $ 9.89 $ 4.47 $ 9.38 $ 4.91 $ 6.02 $ 7.12 $ 2.77 $ 5.18 $ 10.25 $ 5.68 $ 3.59 $ 1.69 $ 3.45 23.4 39.1 45 45 30.3 29.3 46 49 10 11 12 13 14 15 16 17 18 19 20 21 22 29.7 49 52 35 57 58 17.7 20.2 17.7 30.6 39.2 32.7 61 66 37.0 You will need the "Data Analysis" Tool-Pack add-on for Excel to do a regression analysis. If you are unable to download and install this: Windows computer on campus, which already has the add-on installed. Throughout this section, you may refer to lecture video on regr Analysis Add-in Please download the file required for this exercises 1) Colleges Basketball.xlsx We will do a one-variable linear regression with the College Basketball spreadsheet. (Recall that the equation for a one-variable linear regression line is: y = Bo + Bx) 2) Price and Quantity.xlsx A School 2 Duke 3 Michigan State 4 Marquette 5 Kentucky 6 Syracuse 7 Arkansas 8 Connecticut 9 Texas 10 Texas A&M 11 North Carolina 12 Florida 13 lowa 14 Tennessee 15 Memphis 16 Kansas 17 Oklahoma 18 Ohio State 19 Arizona 20 Indiana 21 Wisconsin 22 Alabama 23 UCLA 24 Washington 25 Illinois 26 Pittsburgh 27 California 28 West Virginia 29 Florida State 30 San Diego State 31 Villanova 32 Boston College 33 North Carolina State 34 LSU 35 UAB 36 Wichita State 37 Nevada Data B E Salary Expenses Revenues Winning% 1.40 7.40 12.40 90.00 1.60 6.30 11.00 67.74 1.10 5.80 5.80 66 67 1.90 5.60 12.90 64.52 0 38 5.60 12.40 65.63 0.80 5.60 11.10 72.41 1.50 5.50 7.90 90.00 1.30 5.10 12.00 83.33 0.63 4.90 6.50 74.07 1.40 4.80 15 00 77.78 1.70 4.60 6.50 80.00 0.80 4.50 10.50 73.33 0.80 4.50 5.40 77.78 1.20 4.50 5.60 90.32 1.00 4.30 11.80 75.86 1.00 4.10 6.20 74.07 0.83 4.10 11.40 85.19 0.70 4.10 16.60 63.33 0.78 3.80 11.90 62.96 0.70 3.80 12.00 65.52 1.00 3.70 6.50 60.72 0.91 3.70 7.10 80.65 0.89 3.20 5.00 82.76 0.70 3.20 11.30 83.33 0.49 3.20 7.80 79.31 0.85 3.10 6.00 67.86 0.70 3.10 4.90 66 67 0.74 2.90 6.80 67.86 0.36 2.60 73,33 0.51 2.60 4.20 89 29 0.53 2.50 340 80.00 0.90 2.40 11.40 72.41 0.72 2 20 4.60 75.86 0.60 2.10 1.90 82.14 0.41 2.00 75.00 0.26 1.70 3.30 83.33 2.60 3.10 22 Alabama 23 UCLA 24 Washington 25 Illinois 26 Pittsburgh 27 California 28 West Virginia 29 Florida State 30 San Diego State 31 Villanova 32 Boston College 33 North Carolina State 34 LSU 35 UAB 36 Wichita State 37 Nevada 38 Gonzaga 39 Southern Illinois 40 Northern Iowa 41 Montana 42 Delaware State 43 UNC Wilmington 44 Albany 45 Winthrop 46 Northwestern State B 1.00 0.91 0.89 0.70 0.49 0.85 0.70 0.74 0.36 0.51 0.53 0.90 0.72 0.60 0.41 0.26 0.50 0.21 0.18 0.12 0.19 0.17 0.11 0.20 0.76 C 3.70 3.70 3.20 3.20 3.20 3.10 3.10 2.90 2.60 2.60 2.50 2.40 2.20 2.10 2.00 1.70 1.60 1.30 1.20 1.10 0.91 0.90 0.78 0.74 0.47 D 6.50 7.10 5.00 11.30 7.80 6.00 4.90 6.80 2.60 4.20 3.40 11.40 4.60 1.90 3.10 3.30 2.50 1.20 1.20 1.30 0.91 0.44 0.16 0.52 0.35 60.72 80.65 82.76 83.33 79.31 67.86 66.67 67.86 73.33 89.29 80.00 72.41 75.86 82.14 75.00 83.33 90.00 68.75 71.88 79.31 61.29 78.13 66.67 76.67 77.42 07 Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. How many observations are there in this dataset? Question 2 5 pts Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. What is the equation of the line that the regression analysis produced (write y = Bo + B12, filling in the correct values for the betas) Remember, Bois the intercept coefficient and B, is the coefficient associated with your independent variable. Winning% = 76.86 0.22* Revenues Revenues - 76.86 -0.22* Winning% Winning%--0.22 + 76.86 Revenues Winning% - 76.86 +0.22 Revenues Choose Revenues column to be your independent variable. Then perform a regression analysis with that column as the independent variable and Winning % as the dependent variable. In, this model, is revenue statistically significant? No Yes o o Question 4 2 pt When the confidence limits for slope coefficient are either both positive, or both negative, the slope coefficient must be significantly different from zero. True False In a simple regression model, there is one y-intercept because there is only one independent variable. In multiple regression, there is a y-intercept for each independent variable. True False Question 6 3 pts Is the relationship between Quantity and Price Positive or Negative in the provided data? Negative Positive Run the regression with Price as X variable and Quantity as Y variable. What is the adjusted R-squared in the given data set? Round it to three digits after decimal. Question 8 5 pts Run the regression with Price as X variable and Quantity as Y variable. Using the regression model you make, calculate the predicted Quantity, if price is $6. Round your answer to closest integer. B Income 1 2 3 A Quantity 19 16.0 24 29.3 4 27 13.5 5 30 21.3 6 24 29.1 7 34 27.5 16.2 8 8 39 9 41 27.8 20 14.0 39 Price $ 12.66 $ 7.61 $ 11.08 $ 7.84 $ 8.65 $ 6.32 $ 7.04 $ 8.45 $ 9.89 $ 4.47 $ 9.38 $ 4.91 $ 6.02 $ 7.12 $ 2.77 $ 5.18 $ 10.25 $ 5.68 $ 3.59 $ 1.69 $ 3.45 23.4 39.1 45 45 30.3 29.3 46 49 10 11 12 13 14 15 16 17 18 19 20 21 22 29.7 49 52 35 57 58 17.7 20.2 17.7 30.6 39.2 32.7 61 66 37.0 You will need the "Data Analysis" Tool-Pack add-on for Excel to do a regression analysis. If you are unable to download and install this: Windows computer on campus, which already has the add-on installed. Throughout this section, you may refer to lecture video on regr Analysis Add-in Please download the file required for this exercises 1) Colleges Basketball.xlsx We will do a one-variable linear regression with the College Basketball spreadsheet. (Recall that the equation for a one-variable linear regression line is: y = Bo + Bx) 2) Price and Quantity.xlsx