step by step explanation

1. A study was completed on cholesterol in 100 male adults 40-60 years of age to determine if there is a relationship between cholesterol concentration and time spent watching TV. The researchers wanted to determine if there are any predictive results, such as if the amount of time spent watching TV increases or decreases cholesterol levels. Based on the following regression results, what was the overall study p-value and is it statistically signicant? Variable Model 1 Constant 2.13478 [0.000) Cholesterol 0.023146 {0.001) TV_time 0.044069 [0.002) Adjusted an 0.1426 A. The p-value = 0.003 and is statistically signicant because it is under the 5% level. B. The p-value = 0.003 and is not statistically signicant because it is under the 5% level. C. The p-value = 0.000 and is statistically signicant because it is under the 5% level. D. The p-value = 0.002 and is statistically signicant because it is under the 5% level. 2. Consider a linear regression model where y represents the response variable and all and (12 represent two dummy variables. The model is estimated as 3 = 2.53 + 2.04): + 4.20631 2.86612 + 0.68d1d2. Compute? for x = 3, d1 = 1, and d2 = 0. A. 13.53 B. 3.71 C. 12.85 D. 7.79 3. Sam, a marketing manager for XYZ big box stores, is trying to determine if there is a relationship between shelf space (in feet) and sales (in hundreds of dollars). To do this, Sam selected the top 12 producing locations. Using the provided Model 1 results, what is the estimated equation on Sales? Variable Model 1 Constant 10.365 p-value (0.000) # of shelves 0.211 p-value (0.000) Shelf Space 0.074 p-value (0.001) Adjusted R2 0.6523 A. ^Sales = 10.365 + 0.211shelves + 0.074shelf_space B. ^Sales = -0.211shelves + 0.074shelf_space C. ^Sales = 0.211shelves + 0.074shelf_space D. ^Sales = 0.074shelf_space + (2 x 0.211shelves) 4. Sam, a marketing manager for XYZ big box stores, is trying to determine if there is a relationship between shelf space (in feet) and sales (in hundreds of dollars). To do this, Sam selected the top 12 producing locations. Using the provided Model 1 results, which option best interprets the impact of the coefficients and p-values? Variable Model 1 Constant 10.365 0.000* # of shelves 0.211 0.000* Shelf Space 0.074 0.001* Adjusted R2 0.6523 * the p-value A. The predictor variables are below one offering a negative correlation B. All predictor variables are positive with a significant influence on sales. C. There is no impact presented with the coefficients and p-value results. D. The p-value offers significant influence where the coefficient provides reduction on sales.S. Ava Diego, a doctoral student, is researching car loans issued at a local bank. She prepared a sample of 200 to determine if there is a relationship between the loan amount, length of the loan and interest rate provided. The regression results are in the table below. Which model is more suitable for prediction and what is the best t reason? Variable Model 1 Model 2 Constant 114.325 110.54 0.000 0.000 Interest Rate 106.505 108.650 (0.000) (0.000) Loan Length 0.2074 0.3290 (0.000) (0.005) Interest )1 Loan NA 0.1430 (.0005) Adjusted R2 0.2178 0.2039 A. Model 2 is the most suitable because of the p-value variance. B. Model 1 is the most suitable because of the higher adjusted R2 value. C. Model 2 is the most suitable because of the lower adjusted R2 value. D. Neither provide enough reSults data to predict the model or reasoning. 6. Using a sample of 50, the following regression output is obtained 'om estimating the linear probability regression model y= [30+ 1x+e. What is the predicted probability when x = 14? Standard Coe'icients Error 1' Stat P-value Intercept 4.14 0.30 1.45 0.0001 X -0.02 0.03 -4.65 0.0000 A. 4.42 B. 3.86 C. 8.34 D. 0.72 7. The following table contains the parameter estimates of the linear probability regression model and the logistic regression model. When considering a binary response variable y and two predictor variables, x1 and x2, what is the predicted probability implied by the logistic regression model for x1 = 2 with x2 = 15'? (hint: for logit, the model is = 6Xp(b0 + b1 X71 + b2 2 ) ) 1+exp(b0 + b1 x1 + b2 .172) Linear Variable Probability Logistic Intercept -0.76 -4.1 x1 0.43 1.12 x2 -o.02 -o.22 A. 0.838 B. 0.006 C. -5.16 D. 0.005 8. The following table contains the parameter estimates of the linear probability regression model and the logistic regression model. When considering a binary response variable y and two predictor variables, x1 and x2, what is the predicted probability implied by the logistic probability regression model for x1 = 3 with x2 = 9'? Linear Variable Probability Logistic Intercept -0.76 -1.12 x1 0.43 0.85 x; -0.02 -D.18 A. 1.87 B. 0.35 C. 0.35 D. 0.87