Compute the least-squares regression line for predicting y from x given the following summary statistics. Round the slope and y-intercept decimal places. x=6 sy 1.8 3,-2.3 -30.2 r-0.40 Send date to Excel Regression line equation: -
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- Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $130 million. Use a significance level of α=0.05. A. The regression equation is Y= (Round to one decimal place as needed.) B. The best predicted gross for a movie with a $130 million budget is $ million. (Round to one decimal place as needed.)The following regression model was estimated. Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Rxis the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household in each outlet's immediate service area. Least squares estimation of the regression equation on the basis of the 25 data observations resulted in the estimated regression coefficients and other statistics given in Table below. Variable Coefficient Standard Error of Coefficient Intercept 128832.240 69974.818 Price (P) Competitor Price (Px) | Advertising (Ad) Income () -19875.954 4100.856 15467.936 459.280 0.261 0.094 8.780 1.017 Coefficient of determination R =83.3% (a) Interpret the coefficients of independent variables. (b) Test the significance of independent variables at 5% level of Significance. (c) Interpret R? with the help of adjusted R2. (d) Test for the overall…A researcher is interested to measure returns to schooling. He ran the regression below: w = a + b*School where w is the hourly wage, 'School' measures years of schooling and b is the coefficient on schooling. Fill in the missing blanks to make the statement correct. Omitting an important variable а. biases b only if it is not related to the 'School' variable. b. does not affect the estimate of b. It only affects the standard error of the estimated coefficient. C. biases b and affects the standard error of the estimated coefficient. d. biases b only if it is related to the 'School' variable.
- A statistics professor wants to use the number of hours a student studies for a statistic final exam (x) to predict the final exam score (y). A regression model was fit based on data collected for a class during the previous semester, with the following results: y =35.0 + 3x Which of the following is the correct interpretation of the regression coefficient (slope)? Select the correct response: When the student does not study for the final exam, the mean final exam score is 35.0. None of the above are an interpretation of the slope For each increase of one hour in studying time, the mean change in the final exam score is predicted to be 35.0 For each increase of one hour in studying time, the mean change in the final exam score is predicted to be 3.0.The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.940x + 34. 128. Find the coefficient of determination and interpret the result. 785.8 784.5 1032.7 963.8 1211.5 Money raised, x Money spent, y 456.6 654.6 733.8 449.4 691.4 734.6 764.4 739.3 1018.6 930.3 1172.9 Find the coefficient of determination and interpret the result. 2 = 0.989 (Round to hree decimal places as needed.)The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.
- Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Сoef SE Coef т P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression 3 76501718347 25500572782 Residual Error 96 60109046053 626135896 Total 99 • Is y significantly different from -0.5? Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. Give an interpretation to the term “R-sq" and comment on its value.An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.Find the new data point (x,y) in which x=2 from the data points (1.3) and (4.12)
- Please help me dont do handwritten and explain evry concept and also why other options are incorrect or else please skip...Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sg ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract: The regression equation is Price = B + ÞBedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 s= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression Residual 3 76501718347 25500572782 **** Error 96 60109046053 626135896 Total 99 1. Fill in the missing values *, **, and **** 2. Use the p-value approach to determine if o is significant at the 5% significance level