In a regression analysis involving 25 observations, the following estimated regressionequation was developed.ŷ = 10-18x1 + 3×2 + 14×3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296The test statistic for testing the significance of the model is ___.a. 1.369b. 18.926c. 3.703d. .730

Given observations n= 25 regression equation isŷ = 10 – 18x1 + 3x2 + 14x3 Standard errors and sum of…

Answered: In a regression analysis involving 25…

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 model involved 4 independent variables and 126 observations. The critical value of for testing the significance of each of the independent variable's coefficients will have O A. 130 degrees of freedom OB131 degrees of freedom O C. 125 degrees of freedom O 4 degrees of freedom
Given are five observations for two variables, and y. The estimated regression equation for these data is = 75.74-2.92x. a. Compute SSE, SST, and SSR. Yi The least squares line provided an - Select your answer decimal). fit; 4 SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination ². Comment on the goodness of fit. (to 3 decimals) 00 15 18 20 57 57 46 17 12 Check My Work (2 remaining) % of the variability in y has been explained by the estimated regression equation (to 1 c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)
The following estimated regression equation based on 10 observations was presented. ŷ = 27.1270 +0.5104x₁ + 0.4980x₂ 1 Here, SST = 6,736.125, SSR = 6,222.375, 5b₁ = 0.0813, and = 0.0567. 562
In a regression model involving 30 observations, the following estimated regression equation was obtained.ŷ = 170 + 34x1 – 3x2 + 8x3 + 58x4 + 3x5For this model, SSR = 1,740 and SST = 2,000.The degrees of freedom associated with SSE are _____. a. 6 b. 5 c. 24 d. 19
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A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82
In a regression analysis involving 25 observations, the following estimated regression equation was developed.ŷ = 10 – 18x1 + 3x2 + 14x3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296If we are interested in testing for the significance of the relationship among the variables (i.e., significance of the model), the critical value of F at α = .05 is _____.
2
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.
Is there a way to compute using Excel?
A researcher conducts a multiple regression with Y as the dependent variable and X1, X2, X3 and X4 as explanatory variables. Using the regression output below, fully describe this model and discuss important parts of the output. What is the predicted value of Y if X1 = 3, X2 = 15, X3 = 7 and X4 = 0.003? %3D SUMMARY OUTPUT Regression Staistics Muliple R R Square Adjusted R Square Standard Emor Observations 0.7236 0.5236 0.5159 5.3928 252 ANOVA Significance F 1. 10662E-38 SS MS Regression Residual 1973 9392 29.0820 67.8749 7895.7567 7183.2599 4 247 Total 251 15079.0166 Upper 95% 33.4049 Coefficients Standard Eror t Stat Pvalue 2.2273 0.026830873 Lower 95% 7.9594 2.0508 Intercept X1 17.7278 1.5583 0.2750 5.6662 4.05265E-08 1.0166 2.0999 X2 1.8376 0.1997 9.1999 1.4442 -74708 -3721 4324 1.55861E-17 2.2310 X3 55100 -5.5348 7.94036E-08 -3.5492 X4 -3.1079 1887 8435 -0.0016 0.998687788 3715 2166
In a regression analysis involving 25 observations, the following estimated regression equation was developed.ŷ = 10 – 18x1 + 3x2 + 14x3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296The multiple coefficient of determination is _____. a. .27 b. .73 c. .33 d. .50

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