Given EX = 58, XY = 20, EX² = 576, IY² = 72, XXY = 198 and n = 6 1) The slope of the estimated regression line to 3 decimal places is 2) The intercept of the estimated regression line to 3 decimal places is 3) The standard error of the estimate to 2 decimal places is 4) The standard error of the slope to 3 decimal places is 5) The 90% confidence interval to 3 decimal places is between and 6) Using alpha = 0.05, because the absolute value of the test statistic is

Given EX = 58, XY = 20, EX² = 576, IY² = 72, XXY = 198 and n = 6 1) The slope of the estimated regression line to 3 decimal places is 2) The intercept of the estimated regression line to 3 decimal places is 3) The standard error of the estimate to 2 decimal places is 4) The standard error of the slope to 3 decimal places is 5) The 90% confidence interval to 3 decimal places is between and 6) Using alpha = 0.05, because the absolute value of the test statistic is

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4A: Problems In Applying The Linear Regression Model

Section: Chapter Questions

Problem 2E

See similar textbooks

Similar questions

In the regression model Yi = 30 + B1Xi + B2Di + ß3(Xi × Di) + ui, where X is a continuous variable and D is a binary variable, the slope of the regression is equal to ......, when D= 1. B1+ 33 BO+ B2 31 Xi
Construct a 95% confidence interval for the average value of y for the following data. Use x = 25, se = 4.40, and the equation of the regression line, = 16.394 +0.196x. x 14 21 28 9 20 y 17 16 22 19 26 (Do not round the intermediate values. Round your answers to 2 decimal places, e.g. 0.75.) SE(Y25) s
I estimate a multiple linear regression model with three explanatory variables and a sample size of 363 observations. The RSS of this model is 0.428217, the adjusted R squared is 0.453103. When I regress the depended variable on a constant only, I find that the RSS of this simple model is 0.789537 The value of the realized F stat for the test on the significance of the regression is: Select one: Ⓒa. 100.9721 and the null is that all betas except the intercept are simultaneously equal to zero O b. 145.056123 and the null is that the model is in the overall significant for the population statistically at 1% significance level 145.056123 and the null is that all betas are simultaneously equal to zero Gm. My Moodle O c. O d. 145.056123 and the null is that all betas except the interecpt are simultaneously equal to zero O e. 100.9721 and the null is that all betas are simultaneously equal to zero Clear my choice
(e) Suppose you have been given the following ordinary least squares (OLS) regression result. Estimated Long Run Coefficients using the ARDL Approach ARDL (1,2,2,2,0,2) selected based on Akaike Information Criterion Dependent variable is LY 33 observations used for estimation from 1987 to 2019 T-Ratio [Prob.] 4.6671[0.000] 4.6678[0.051] 7.9897[0.043] -4.802[0.009] 2.3898[0.028] 1.0498[0.308] Regressor Coefficient Standard Error 0.36068 0.45447 LK 0.077280 LM 0.097363 0.48751 -0.41208 0.19057 0.52521 LE 0.061017 LF 0.085800 LT 0.079744 C 0.500320 where, Y = Economic growth K = Capital M = Employment E = Electricity consumption F = Foreign direct investment T= Technology (i) Write the regression equation. Interpret the estimated coefficients. (ii) Which explanatory variables are significant at the 1%, 5% and 10% level? Which variables are insignificant? Briefly explain.
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was ŷ = 83.7 + 2.23x1 + 1.60x2. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.445. (a)Compute and interpret R2 and Ra2.(Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (??) . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (??).
You extract approximately 5,000 observations from the Current Population Survey (CPS) and estimate the following regression function: AHE= 3.32 -0.45 x Age, R² =0.02, SER= 8.66 (1.00) (0.04) where AHE is average hourly earnings, and Age is the individual's age. Given the specification, your 95% confidence interval for the effect of changing age by 5 years is approximately: OA. [$2.32, $4.32]. B. [$1.86, $2.64]. C. [$1.35, $5.30]. D. Cannot be determined given the information provided.
In regression analysis, the existence of a significant pattern in successive values of the error term constitutes:
You are given the following data: The regression equation is: A. -0.66 B. -1.20 (X'X)*¹ C. 1.12 O D. 2.06 = 1.3 2.1 0.8 -1.4 1.9 2.1 -1.4 s² = 0.86. T = 103 The correlation between ₁ and 3 (i.e., corr(Â₁, Â3)) is: -1.6] 1.9 (X'y) = 2.9 3.4 0.8 Yt = B₁ + B₂X2+ + B3X3t + Ut.
Consider a data set with 15 observations and consider a multiple linear regression model with 7 in-dependent variables. Assume you have estimated the model and you find that SST = 1,325 and SSR = 794.
An attempt was made to evaluate the inflation rate as a predictor of the spot rate in the German treasury bill market. For a sample of 79 quarterly observations, the estimated linear regressionŷ = 0.0027 + 0.7916xwas obtained, wherey = actual change in the spot ratex = change in the spot rate predicted by the inflation rateThe coefficient of determination was 0.097, and the estimated standard deviation of the estimator of the slope of the population regression line was 0.2759.a. Interpret the slope of the estimated regression line.b. Interpret the coefficient of determination.c. Test the null hypothesis that the slope of the population regression line is 0 against the alternative that the true slope is positive, and interpret your result.d. Test, against a two-sided alternative, the null hypothesis that the slope of the population regression line is 1, and interpret your result.
Consider the linear regression model Y; = Bo + B1X; + U; for each i = 1, ..., n, with n large. Let B1.n be the OLS estimate of B1. Let c be such that Pr(Bn > c) = 0.005. The 99% confidence interval for B1 is •••) C O (B1,n – SE(Ŝ1,n) × c, B1,n + SE(Ŝ1,m) × c). O IB1,n – 2 x SE(Î1,n) × c, B1,n + 2 × SE(Ŝ1,n) × c). O l31,n – c, Bì,n + c]. O B1,n – 2c, B1,n + 2c]. -
A website that rents movies online recorded the age and the number of movies rented during the past month for some of their customers. The data are shown below for a random sample of 25 of their customers.The regression line for the data, with number of movie rentals as the response variable, provides an intercept = 18.87, and slope = -0.228. The standard error of the slope SE(b1) = 0.0827. Margin of error ME for a 99% Confidence Interval for the slope of the Population regression line is: 0.1161 0.2322 0.4644 0.3483