(to 4 decimals)d. Use the t-test to test the following hypotheses (a = 0.10):Ho: B1 = 0Ha: B1 +0Compute the value of the t-test statistic (Enter negative values as negative numbers).(to 3 decimals)What is the p-value? Use Table 2 from Appendix B.p-value is - Select your answer -What is your conclusion?We - Select your answer - v Ho.e. Use the F-test to test the hypotheses in part (d) at a 0.10 level of significance.Complete the F table below using Excel. Calculate the Sum of Squares (to 1 decimal), the Mean Squares (to 1 decimal), and the F ratio (to 2 decimals) and the p-value (to 4decimals).SourceDegreesSum ofМeanof Variationof FreedomSquaresSquarep-valueRegressionErrorTotalWhat is your conclusion, based on this F test?WeSelect your answerv Ho. Given are tive observations for two variables, x and y.1418205554422315Use the estimated regression equation: ŷ = 68.1654 – 2.4488x.a. Compute the mean square error using equation.SSE2 = MSE :n- 2(to 4 decimals)b. Compute the standard error of the estimate using equation.SSE/MSEп - 2(to 4 decimals)c. Compute the estimated standard deviation of bị using equation.(to 4 decimals)d. Use the t-test to test the following hypotheses (a = 0.10):Ho: B1 = 0Ha: B1 +0Compute the value of the t-test statistic (Enter negative values as negative numbers).(to 3 decimals)What is the p-value? Use Table 2 from Appendix B.

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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=-1.063 b=24.198 r2=0.559504 r=-0.748 Use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place).
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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%3ax+b a=-1.219 b=29.882 r2=0.727609 r=-0.853 Use this to predict the number of situps a person who watches 11 hours of TV can do (to one decimal place)
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=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
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=-0.71 b=27.318 r2=0.891136 r=-0.944 Use this to predict the number of situps a person who watches 12.5 hours of TV can do (to one decimal place)
Run a regression analysis on the following data set, where y is the final grade in a math class and x is the average number of hours the student spent working on math each week. hours/week Grade y 8. 72.2 8. 58.2 10 60 11 71.4 14 92.6 14 76.6 14 75.6 14 83.6 15 81 20 100 State the regression equation with constants accurate to 2 decimal places. ý = What is the predicted value for the final grade when a student spends an average of 15 hours each week on math? Round to 2 decimal places. Question Help: D Video 1 Video 2 Submit Question
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= -0.889 b=32.071 r2=0.505521 r= -0.711 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Predictor Coef SE Coef t-ratio Constant Arm span -7.611 2.567 2.965 0.046 0.186 0.035 5.377 0.000 S = 1.61 R-Sq = 63.0% R-Sq (Adj) = 64.9% Which of the following is the best interpretation of the standard deviation of the residuals? The typical arm span is 161 centimeters. The typical foot length is 16.1 centimeters. The typical distance between the observed and predicted arm spans is 1.61 centimeters. The typical distance between the observed and predicted foot lengths is 1.61 centimeters. Op
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=-0.794 b=31.311 r²=0.9801 r=-0.99 Use this to predict the number of situps a person who watches 8 hours of TV can do (to one decimal place)
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.

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