pls help solve i am struggling, number 23 table is at the end

QUESTION 20 Art investigator hired by a dient suing for gender discrimination has developed a multiple regression model for employee salaries for the company in question. In this regression model the salaries are in thousands of dollars. Salaries are annual. For example, a data entry of 5 for the dependent variable indicates a salary of $35.000 year. The Indicator (dummy) variable for gender is coded as X - if male and X4 - 1 if female. The Data Analysis output of this mumple regression model shows that coefficient (1) for this variable ) is -4 2. The test showed that X, was significant at 0.1. This result implies that for male and female workers of the company on the average women earn 54,200 less than men. QUESTION 21 Adding any independent variable to a multiple regression model while keeping the sample size constant will artificially increase R-square we interpret the adjusted R-square as it adjusts for the number of variables and the sample size used in the model in multip QUESTION if the correction between two Independent variables is greater than 80, then we consider the model to exhibit multicollinearity QUESTION 2 QUESTION 24 THE HOUSING SALES CASE Select the choice that correctly interprets the meaning of the coefficient (b) corresponding to the variable number of bedrooms in the context of the probiert For every additional bedroom the price of the house is expected to increase by about $129. Holding the size of the house and the condition of the roof constant for every additional bedroom the price of the house is expected to decrease by about 511 For every additional bedroom the price of the house is expected to decrease by about 5128. Holding the size of the house and the condition of the roof constant for every additional bedroom the price of the house is expected to increase by about 511 QUESTION 25 THE HOUSING SALES CASE Select the choice the cornerpress the mean of the coefficient of the dummy variable "D2 New Holding the of the house and the number of bedrooms constant houses with new roof are expected to sell for about 520,945 more than houses with conditio Holdin the star of the house and the number of bedrooms constant, houses with new roof are expected to sell for about $20.945 more than houses with cond Hou with new roof are expected to sell for about $20.945 more than houses with poor roof condition. How with new roof are expected to sell for about $20.945 more than houses with acceptable roof condition. LA QUESTION 26 THE HOUSING SALES CASE is number of bedrooms a good predictor for the sales price of a house Conduct an acconciate hypothesis test and select the word that correctly completes the conclusion There is no evidence to conclude that number of bedrooms is a good predictor of the sales price of a house in Cleveland white QUESTION 27 THE HOUSING SALES CASE Predict the price of a house that has 2.000 square feet. 3 bedrooms, and a poor roof condition sales price in 51.000) round your answer to the nearest whole 209991 QUESTION 20 THE HO! Estimate with confidence the moun priekouses that have 2000 square feet, 3 bedrooms and poor roof condition. Interpret the meaning of the context of the problem QUESTION 26 THE HOUSING SALES CASE is number of bedrooms a good predictor for the sales price of a house Conduct an anoreciate hypothesis test and select the word that correctly complete se conclusion There is no evidence to conclude that number of bedrooms is a good predictor of the sales price of a house in Cleveland Heights QUESTION 27 THE HOUSING SALES CASE Predict the price of a house that has 2.000 square feet, 3 bedrooms and a poor roof condition, sales pnce in 51.000 round your answer to the nearest whole 209991 QUESTION 23 THE HOEALES CASE Estimat with confidence the mean pricelouses that have 2000 square feet 3 bedrooms and poor roof condition. Interpret the meaning of the context of the problem mer QUESTION 2 THE HOUSING SALES CASE Estimate with or confidence the mean price of all houses that have 2000 square feet, 3 bedrooms and poor root condition, interpret the meaning of the intervalinth context of the problem Hint Find the end of the interval THAN consider that sale price is in 51.000 We are 90% confident that the mean price of all houses that have 2000 square feet 3 bedrooms and poor roof condition is anywhere between 1191791 and 521 We are confident that the price of a signie house of 2000 square feet with 3 bedrooms, and poor roof condition is anywhere between 5190.791 und 1215.7 We are confidence that the mean price of all houses that have 2000 square feet 3 bedrooms and poor roof condition is anywhere between $107.835 and We are on confident that the mean price of all houses that have 2000 square feet, 3 bedrooms and poor roof condition is anywhere between 5162.796 and 5 QUESTION 29 THE HOUSING SALES CASE Predict with 90% confidence of one house that has 2000 square feet 3 bedrooms and poor roof condition. Select the interpretation of the results an the interval in the context of the problem Hint Find that of the interval ma consider that eles posin 59.000 with contidence we can expect a house that was 2000 square feet 3 bedrooms and poor roof condition will sell for between S162.785 and 52:52.795 with confidence we can expect a house that as 2000 square feet. 3 bedrooms and poor roof condition will sell for between 5185.464 and 523011 without confidence we can expect a house that was 2000 square feet. 3 bedrooms and poor roof condition will sell for between $179,760 and $277.71 Wit 20% conlidence we can expect a house that has 2000 square feet 3 bedrooms and poor roof condition will sell for between $209,391 and 5248.00 QUESTION 30 THE HOUSING SALES CASE Select the statement that correctly reports and interpret the Adjusted square) Adjusted R2 - 768 76.5 of variability in sales price of Cleveland Heights houses can be explained the size of the house, the number of bedrooms and the condit the roof. Adjusted R2 - 807: 80.7 After adjusting for the sample size and number of variables used in the model. 76.84 of variability in sales price of Cle landets can be explained the size of the house, the number of bedrooms, and the condition of the root. Adjusted R2-807; 30.7% of variability in sales price of Cleveland Heights houses can be explained the size of the house, the number of bedrooms and the cor the roof. Adjusted R2 - 768: After adjusting for the sample size and number of variables used in the model. 76.8% of variability in sales price of Cleveland Heights hous explained the size of the house, the number of bedrooms, and the condition of the roof. QUESTION 31 THE HOUSINS What statercoyou make about the calculated statistic Fcalculated) and the significance of the overall model at a - 05? Fcalculate 2032 with conndence was conclude that the model is usefut at predicting the price of houses in Cleveland Heights Cleveland Heights Jimmy uses the sue of the house in square feet the number of bedrooms and the condition of the root onder wants to sales price of a house my classified the condition of the root as poor, acceptable and new, and of conditions the bus when creating the dummy in THE HOUSING SALES CASE questions that follow prome to use values from the beat below when posible precious time calculating values that are already available in the output provided This rection tout is populated in the third word of the excel document SUMMARY OUTPUT Regression Statistics Multiple R 0.89819831 R Square 0.80676021 Adjusted R Square 0.76811225 Standard Error 26.0871514 Observations 25 ANOVA df Regression Residual Total 55 56823.92 13610.79 7049 MS F Significance F 4 14205.98106 20.87459 6.58352E-07 20 680.539468 intercept square fee number of bedrooms 01 - Acce D2 New Gardients Standard ror Stot P.value 12.00 40020524 -0.30594704 0.718247 0.021260706 6.082.834279 6.31E-06 11578235 -0.97642374 0.340518 19.129827 20.169007 0.948473589 0.354209 20.151023 23.5653587 1.544184753 0.13822 Lower 95% Upper 95% -107.8356247 75.64674321 0.084551081 0.173249192 -35.45719285 12.84656734 -22.9421093 61.20176429 -7.348609479 49.23881606 QUESTION 20 Art investigator hired by a dient suing for gender discrimination has developed a multiple regression model for employee salaries for the company in question. In this regression model the salaries are in thousands of dollars. Salaries are annual. For example, a data entry of 5 for the dependent variable indicates a salary of $35.000 year. The Indicator (dummy) variable for gender is coded as X - if male and X4 - 1 if female. The Data Analysis output of this mumple regression model shows that coefficient (1) for this variable ) is -4 2. The test showed that X, was significant at 0.1. This result implies that for male and female workers of the company on the average women earn 54,200 less than men. QUESTION 21 Adding any independent variable to a multiple regression model while keeping the sample size constant will artificially increase R-square we interpret the adjusted R-square as it adjusts for the number of variables and the sample size used in the model in multip QUESTION if the correction between two Independent variables is greater than 80, then we consider the model to exhibit multicollinearity QUESTION 2 QUESTION 24 THE HOUSING SALES CASE Select the choice that correctly interprets the meaning of the coefficient (b) corresponding to the variable number of bedrooms in the context of the probiert For every additional bedroom the price of the house is expected to increase by about $129. Holding the size of the house and the condition of the roof constant for every additional bedroom the price of the house is expected to decrease by about 511 For every additional bedroom the price of the house is expected to decrease by about 5128. Holding the size of the house and the condition of the roof constant for every additional bedroom the price of the house is expected to increase by about 511 QUESTION 25 THE HOUSING SALES CASE Select the choice the cornerpress the mean of the coefficient of the dummy variable "D2 New Holding the of the house and the number of bedrooms constant houses with new roof are expected to sell for about 520,945 more than houses with conditio Holdin the star of the house and the number of bedrooms constant, houses with new roof are expected to sell for about $20.945 more than houses with cond Hou with new roof are expected to sell for about $20.945 more than houses with poor roof condition. How with new roof are expected to sell for about $20.945 more than houses with acceptable roof condition. LA QUESTION 26 THE HOUSING SALES CASE is number of bedrooms a good predictor for the sales price of a house Conduct an acconciate hypothesis test and select the word that correctly completes the conclusion There is no evidence to conclude that number of bedrooms is a good predictor of the sales price of a house in Cleveland white QUESTION 27 THE HOUSING SALES CASE Predict the price of a house that has 2.000 square feet. 3 bedrooms, and a poor roof condition sales price in 51.000) round your answer to the nearest whole 209991 QUESTION 20 THE HO! Estimate with confidence the moun priekouses that have 2000 square feet, 3 bedrooms and poor roof condition. Interpret the meaning of the context of the problem QUESTION 26 THE HOUSING SALES CASE is number of bedrooms a good predictor for the sales price of a house Conduct an anoreciate hypothesis test and select the word that correctly complete se conclusion There is no evidence to conclude that number of bedrooms is a good predictor of the sales price of a house in Cleveland Heights QUESTION 27 THE HOUSING SALES CASE Predict the price of a house that has 2.000 square feet, 3 bedrooms and a poor roof condition, sales pnce in 51.000 round your answer to the nearest whole 209991 QUESTION 23 THE HOEALES CASE Estimat with confidence the mean pricelouses that have 2000 square feet 3 bedrooms and poor roof condition. Interpret the meaning of the context of the problem mer QUESTION 2 THE HOUSING SALES CASE Estimate with or confidence the mean price of all houses that have 2000 square feet, 3 bedrooms and poor root condition, interpret the meaning of the intervalinth context of the problem Hint Find the end of the interval THAN consider that sale price is in 51.000 We are 90% confident that the mean price of all houses that have 2000 square feet 3 bedrooms and poor roof condition is anywhere between 1191791 and 521 We are confident that the price of a signie house of 2000 square feet with 3 bedrooms, and poor roof condition is anywhere between 5190.791 und 1215.7 We are confidence that the mean price of all houses that have 2000 square feet 3 bedrooms and poor roof condition is anywhere between $107.835 and We are on confident that the mean price of all houses that have 2000 square feet, 3 bedrooms and poor roof condition is anywhere between 5162.796 and 5 QUESTION 29 THE HOUSING SALES CASE Predict with 90% confidence of one house that has 2000 square feet 3 bedrooms and poor roof condition. Select the interpretation of the results an the interval in the context of the problem Hint Find that of the interval ma consider that eles posin 59.000 with contidence we can expect a house that was 2000 square feet 3 bedrooms and poor roof condition will sell for between S162.785 and 52:52.795 with confidence we can expect a house that as 2000 square feet. 3 bedrooms and poor roof condition will sell for between 5185.464 and 523011 without confidence we can expect a house that was 2000 square feet. 3 bedrooms and poor roof condition will sell for between $179,760 and $277.71 Wit 20% conlidence we can expect a house that has 2000 square feet 3 bedrooms and poor roof condition will sell for between $209,391 and 5248.00 QUESTION 30 THE HOUSING SALES CASE Select the statement that correctly reports and interpret the Adjusted square) Adjusted R2 - 768 76.5 of variability in sales price of Cleveland Heights houses can be explained the size of the house, the number of bedrooms and the condit the roof. Adjusted R2 - 807: 80.7 After adjusting for the sample size and number of variables used in the model. 76.84 of variability in sales price of Cle landets can be explained the size of the house, the number of bedrooms, and the condition of the root. Adjusted R2-807; 30.7% of variability in sales price of Cleveland Heights houses can be explained the size of the house, the number of bedrooms and the cor the roof. Adjusted R2 - 768: After adjusting for the sample size and number of variables used in the model. 76.8% of variability in sales price of Cleveland Heights hous explained the size of the house, the number of bedrooms, and the condition of the roof. QUESTION 31 THE HOUSINS What statercoyou make about the calculated statistic Fcalculated) and the significance of the overall model at a - 05? Fcalculate 2032 with conndence was conclude that the model is usefut at predicting the price of houses in Cleveland Heights Cleveland Heights Jimmy uses the sue of the house in square feet the number of bedrooms and the condition of the root onder wants to sales price of a house my classified the condition of the root as poor, acceptable and new, and of conditions the bus when creating the dummy in THE HOUSING SALES CASE questions that follow prome to use values from the beat below when posible precious time calculating values that are already available in the output provided This rection tout is populated in the third word of the excel document SUMMARY OUTPUT Regression Statistics Multiple R 0.89819831 R Square 0.80676021 Adjusted R Square 0.76811225 Standard Error 26.0871514 Observations 25 ANOVA df Regression Residual Total 55 56823.92 13610.79 7049 MS F Significance F 4 14205.98106 20.87459 6.58352E-07 20 680.539468 intercept square fee number of bedrooms 01 - Acce D2 New Gardients Standard ror Stot P.value 12.00 40020524 -0.30594704 0.718247 0.021260706 6.082.834279 6.31E-06 11578235 -0.97642374 0.340518 19.129827 20.169007 0.948473589 0.354209 20.151023 23.5653587 1.544184753 0.13822 Lower 95% Upper 95% -107.8356247 75.64674321 0.084551081 0.173249192 -35.45719285 12.84656734 -22.9421093 61.20176429 -7.348609479 49.23881606