What is the difference between using robust standard errors for hypothesis testing versus the homoskedastic only case?Robust standard errors ensure we have an unbiased estimation of our OLS slope coefficient.a.b Robust standard errors account for potential heteroskedasticity in the variation of the cross-sectional units.None of theseC.Robust standard errors are usually equal to standard errors in the homoskedastic case.d.Robust standard errors are used in the case that variance is constant in the data. Which of the following is a good indication that nonlinear terms might be necessary as control varlables?A clear, nonlinear relationship in the residuals.a.b.Failure to reject the null that the variable of interest is 0.None of these.C.When the correlation is weak between the varlables.d.e A clear, nonlinear relationship when plotting the data of the regressors.

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Answered: What is the difference between using…

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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If the coefficient B₁ has a nonzero value, then it is helpful in predicting the value of the response variable. If B₁ = 0, it is not helpful in predicting the value of the response variable and can be eliminated from the regression equation. To test the claim that B₁ = 0 use the test statistic t = (b₁-0) /sp. Critical values or P-values can be found using the t distribution with n - (k+1) degrees of freedom, where k is the number of predictor (x) variables and n is the number of observations in the sample. The standard error sp, is often provided by software. For example, see the accompanying technology display, which shows that sp=0.076885101 (found in the column with the heading of "Std. Err." and the row corresponding to the first predictor variable of height). Use the technology display to test the claim that B₁ = 0. Also test the claim that B₂ = 0. What do the results imply about the regression equation? Click the icon to view the technology output. Test the claim that B₁ = 0. For…
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An article in International Journal of Electrical Power & Energy Systems {"Stochastic Optimal Load Flow Using a Combined Quasi- Newton and Conjugate Gradient Technique" (1989, Vol. 11(2), pp. 85-93)} considered the problem of optimal power flow in electric power systems and included the effects of uncertain variables in the problem formulation. The method treats the system power demand as a normal random variable with 0 mean and unit variance. What is the power demand value that is exceeded with 8096 probability? Round your answer to two decimal places (e.g. 98.76). Ancwor ic Rlanlk 1
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4) In a univariate linear regression, explain intuitively, graphically and mathematically, how the variance of the estimated slope depends on a) the number of observations; b) the mean squared deviation of the independent variable; c) What else does it depend on? Can you explain how?
The breaking strengths of cables produced by a certain company are approximately normally distributed. The company announced that the mean breaking strength is 2140 pounds with a variance of 32,761. A consumer protection agency claims that the actual variance is higher. Suppose that the consumer agency wants to carry out a hypothesis test to see if its claim can be supported. State the null hypothesis Ho and the alternative hypothesis H₁ they would use for this test. Ho: H₁: 0 μ OSO 0=0 X X Р ☐#0 S O0 020
2. In building an arena, steel bars with a mean ultimate tensile strength of 400 Megapascal (MPa) with a variance of 81 MPa were delivered by the manufacturer. The project engineer tested 50 steel bars and found out that the mean ultimate tensile strength is 390 MPa. The decision for the extension of the contract with the manufacturer depends on the engineer. Test the hypothesis whether there is no significant difference between the two means using a two - tailed with a = 0.01.
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An engineer has designed a valve that will regulate water pressure on an automobile engine. The valve was tested on 260 engines and the mean pressure was 4 lbs/square inch. Assume the variance is known to be 0.64. If the valve was designed to produce a mean pressure of 4.1 lbs/square inch, is there sufficient evidence at the 0.02 level that the valve does not perform to the specifications? State the null and alternative hypotheses for the above scenario.
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