Consider the following multiple regressionPrice = 118.8 + 0.554BDR+23.8Bath +0.144Hsize +0.005Lsize +0.104Age - 48.8Poor, R² = 0.79, SER = 41.1(0.00046) (0.382) (10.9)(23.8)(2.69) (8.92)(0.016)The numbers in parentheses below each estimated coefficient are the estimated standard errors. A detailed description of the variables used in the data set is available here iSuppose you wanted to test the hypothesis that BDR equals zero. That is,Report the t-statistic for this test.Is the coefficient on BDR statistically different from zero at the 5% significance level?A. Yes.B. No.Ho: BDR=0 vs H₁: BDR#0A. Yes.B. No.The t-statisticis 0.206(Round your response to three decimal places)Typically five-bedroom houses sell for much more than two-bedroom houses. Is this consistent with your previous answer and with the regression more generally?A homeowner purchases 2391 square feet from and adjacent lot. Construct a 95% confidence interval for the change in the value of her house.The 95% confidence interval for the change in the value of the home is(Round your response to two decimal places)

Given that,to construct a 95% confidence interval for the change in the value of the homeFor a 95%…

Answered: Consider the following multiple…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y-ax+b a=-1.108 b-34.092 r2-0.736164 r=-0.858 Assume the correlation is significant, and use this to predict the number of situps a person who watches 4 区 hours q TV can do (to one decimal place) 72222392 口 D
For a multiple regression analysis with 2 and 12 degrees of freedom, MS regression is 135 and MS residual is 15. What is the decision for this test?
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.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05 Right Arm 101 100 94 75 Left Arm 174 167 146 144 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is (Round to one decimal place as needed.) 76 144 CRITS
The regression analysis shows that r^2 = 0.4688. What would the correlation be? A. r = √0.4688 B. r = −√0.4688 C. Both A and B. D. None of the above.
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y).The results of the regression were: y=ax+b a=5.088 b=26.56 r2=0.913936 r=0.956 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (X) and the test scores (y ). The results of the regression were:y=ax+ba=5.931b=20.1r2=0.748225r=0.865Use this to predict the final exam score of a student who studies 3 hours per week, and please round your answer to a whole number.
Use the estimate yest=3.3x2 - 9.4x - 0.1 to calculate a set of residuals, using a formula or a calculator. Explain your steps, then create a residual plot using this new model and assess its validity
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.
please please answer fast please please answer super super fast
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.
П. 2. What is the degrees of freedom in a multiple regression model( with n values in each variable) with 14 independent variables when doing a t-test for the individual regression coefficients determined?

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