Ch 17 multiple regression1. In a multiple regression analysis, if the model provides a poor fit, this indicates that:a. the sum of squares for error will be large.b. the standard error of estimate will be large.c. the coefficient of determination will be close to zero.d. All of these choices are true.2. Suppose a multiple regression analysis involving 25 data points has -18 and SSE = 36. Then, thenumber of the independent variables must be:a. 6b. 5C. 4d. 33. In a multiple regression model, the mean of the probability distribution of the error variable e isassumed to be:a. 1.0b. 0.0e. k, where k is the number of independent variables included in the model.d. None of these choices.4. The adjusted coefficient of determination is adjusted for the:a. number of regression parameters including the y-intercept.b. number of dependent variables and the sample size.c. number of independent variables and the sample size.d. coefficient of correlation and the significance level.5. In a multiple regression model, the standard deviation of the error variable e is assumed to be:a. constant.b. 0.c. 1.0.d. None of these choices.6. In multiple regression analysis, the ratio MSR/MSE yields the:a. 1-test statistie for testing each individual regression coefficient.b. F-test statistic for testing the validity of the regression equation.c. coefficient of determination.d. adjusted coefficient of determination.7. In a multiple regression analysis involving 6 independent variables, the total variation in y is 900 andSSR - 600. What is the value of SSE?a. 300b. 1.50e. 0.67d. None of these choices.8. In order to test the validity of a multiple regression model involving 5 independent variables and 30observations, the numerator and denominator degrees of freedom for the critical value of Fare,respectively,a. 5 and 30b. 6 and 29e. S and 24d. 6 and 25

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MATLAB: An Introduction with Applications

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Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Use the technology of your choice to do the following. a. Use the maximum- R2 criterion to obtain a regression equation for these data. b. Use the adjusted- R2 criterion to obtain a regression equation for these data. c. Use the Mallows’ Cp criterion to obtain a regression equation for these data. d. Are the regression equations obtained in parts (a), (b), and (c) the same? e. Use the analysis in parts (a), (b), and (c) to select a regression equation for these data. For the regression equation that you selected, obtain plots of residuals versus fitted values, residuals versus the included predictor variables, and a normal probability plot of the residuals. Perform a residual analysis to assess the appropriateness of the regression equation, constancy of the conditional standard deviations, and normality of the…
Q.1/ Use linear regression to fit the following experimental data. 图 2 3 4 5 7 10 y 5.2 7.8 10.7 13 19.3 26.5
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1. In a multiple regression analysis, if the model provides a poor fit, this indicates that: a. the sum of squares for error will be large. b. the standard error of estimate will be large. e. the coefficient of determination will be close to zero. d. All of these choices are true. Suppose