O Given are five observations for two variables, x and y. Excel File: data14-25.xlsx 6 9 13 20 Yi 7 18 9 26 23 The estimated regression equation is y = 7.6+ 0.9x. a. What is the value of the standard error of the estimate (to 4 decimals)? b. Test for a significant relationship by using the t test. Use a = 0.05. What is the value of the t test statistic (to 2 decimals)? What is the p-value? Use Table 2 of Appendix B. - Select your answer - What is your conclusion (a = 0.05)? Select your answer - c. Use the F test to test for a significant relationship. Use a = 0.05. Compute the value of the F test statistic (to 2 decimals). What is the p-value? Use Table 4 of Appendix B. Select your answer - What is your conclusion? - Select your answer -

O Given are five observations for two variables, x and y. Excel File: data14-25.xlsx 6 9 13 20 Yi 7 18 9 26 23 The estimated regression equation is y = 7.6+ 0.9x. a. What is the value of the standard error of the estimate (to 4 decimals)? b. Test for a significant relationship by using the t test. Use a = 0.05. What is the value of the t test statistic (to 2 decimals)? What is the p-value? Use Table 2 of Appendix B. - Select your answer - What is your conclusion (a = 0.05)? Select your answer - c. Use the F test to test for a significant relationship. Use a = 0.05. Compute the value of the F test statistic (to 2 decimals). What is the p-value? Use Table 4 of Appendix B. Select your answer - What is your conclusion? - Select your answer -

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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A large school district is reevaluating its teachers' salaries. They have decided to use regression analysis to predict mean teacher salaries at each elementary school. The research has come up with the following prediction equation: Y = $18012.24 + 1432.37X1 - 4.07 X2 where X1 = Yrs Exp and X2 = Yrs Exp2 (a) If a teacher has 7 years of experience, what is the expected salary? (b) If teacher has 10 years of experience, what is the expected salary?
In exercise 1, the following estimated regression equation based on 10 observations was presented. y^=29.1270+.5906x1+.4980x2Here SST=6724.125, SSR=6216.375, sb1=.0813, and sb2=.0567. a) Compute MSR and MSE. b) Compute F and perform the appropriate F test. Use α=.05. c) Perform a t test for the significance of β1. Use α=.05. d) Perform a t test for the significance of β2. Use α=.05.
In an OLS regression, which value represents the "best" R2 in terms of explained variance in the dependent variable? A. 2.53 B. 16.22 C. .001 D. 0.53
Regression Statistics Multiple R 0.971 R-Square A Adjusted R-Square .942 Standard Error 30.462 Observations 51 ANOVA df SS MS F Significance F Regression C 747851.57 373925.79 402.98 9.89E-31 Residual 48 D 927.91 Total 50 792391.11 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept E 62.13 26.79 1.60E-30 1539.66 1789.51 Price of Roses −6.68 F −1.41 1.64E-01 −16.16 2.81 Disposable Income (M) 9.73 0.34 G 1.23E-31 9.04 10.42…
A regression of average weekly earnings (AWE, measured in dollars) on age(measured in years) using a random sample of college-educated full-timeworkers aged 25–65 yields the following: AWE = 696.7 + 9.6 X Age, R2 = 0.023, SER = 624.1.a. Explain what the coefficient values 696.7 and 9.6 mean.b. The standard error of the regression (SER) is 624.1. What are the unitsof measurement for the SER? (Dollars? Years? Or is SER unit-free?)c. The regression R2 is 0.023. What are the units of measurement for theR2? (Dollars? Years? Or is R2 unit-free?)d. What does the regression predict will be the earnings for a 25-year-oldworker? For a 45-year-old worker?e. Will the regression give reliable predictions for a 99-year-old worker?Why or why not?f. Given what you know about the distribution of earnings, do youthink it is plausible that the distribution of errors in the regressionis normal? (Hint: Do you think that the distribution is symmetric orskewed? What is the smallest value of earnings,…
Consider the following multiple regression Price=118.9+0.594BDR+23.5Bath+0.195Hsize+0.004Lsize+0.095Age−48.5Poor, R2=0.75, SER=41.5 (22.7) (2.56) (8.56) (0.017) (0.00049) (0.315) (10.7) 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 . Suppose you wanted to test the hypothesis that BDR equals zero. That is, H0: BDR=0 vs H1: BDR≠0 Report the t-statistic for this test. The t-statistic is ________ (Round your response to three decimal places)
The following data gives the experience of the machine operators and their performance ratings as given by the number of good parts turned out per 100 pieces.Experience(X) 16 12 18 4 3 10 5 12Performance Ratings (Y) 88 87 89 68 78 80 75 83Obtain the regression line of performance ratings on experience and estimate the probable performance if the operator has 7 years of experience.
Given the following regression output, Predictor Coefficient SE Coefficient t p-value Constant 84.998 1.863 45.62 0.000 x1 2.391 1.200 1.99 0.051 x2 -0.409 0.172 -2.38 0.021 Analysis of Variance Source DF SS MS F p-value Regression 2 77.907 38.954 4.138 0.021 Residual Error 62 583.693 9.414 Total 64 661.600 answer the following questions: d-1. State the decision rule for 0.05 significance level: H0: β1 = β2 = 0; H1: Not all β's are 0. (Round your answer to 2 decimal places.) d-2. Compute the value of the F statistic. (Round your answer to 2 decimal places.) d-3. What is the conclusion? Use the 0.05 significance level.
Suppose you have a large, random sample of the variables Y and X. You then regress Y on X and get the following results (with standard errors in parentheses): Y=16.8-3.9x (3.8) (1.2) The numbers 16.8 and -3.9 are the realized values for the intercept and slope (respectively) of the regression equation describing the sample, which are consistent estimators for what population parameters? The intercept and slope (respectively) of the sample determining function. The intercept and slope (respectively) of the regression equation that best fits the population. Instructions: Enter your responses rounded to three decimal places. If you are entering any negative numbers be sure to include a negative sign (-) in front of those numbers: b. Provide a 99% confidence interval for each estimator's corresponding population parameter: Intercept: Slope:(------------) (-------------) Slope (-------------) (------------------)
Given the following regression output, Predictor Coefficient SE Coefficient t p-value Constant 84.998 1.863 45.62 0.000 x1 2.391 1.200 1.99 0.051 x2 -0.409 0.172 -2.38 0.021 Analysis of Variance Source DF SS MS F p-value Regression 2 77.907 38.954 4.138 0.021 Residual Error 62 583.693 9.414 Total 64 661.600 answer the following questions: Write the regression equation. (Round your answers to 3 decimal places. Negative values should be indicated by a minus sign.) If x1 is 4 and x2 is 11, what is the expected or predicted value of the dependent variable? (Round your answer to 3 decimal places.) How large is the sample? How many independent variables are there?
Consider the regression model Yi = b0 + b1X1i + b2X2i + ui. Use approach 2from Section 7.3 to transform the regression so that you can use a t-statistic to testa. b1 = b2.b. b1 + 2b2 = 0.c. b1 + b2 = 1. (Hint: You must redefine the dependent variable in theregression.)
Suppose you run a regression y=alpha + beta*x + u. You know that the estimated coefficient is 2.94 and the standard error is 1.09. What is the value of t-statistic for your estimated coefficient beta?