Question 16 ( Suppose the error variance is a linear function of the explanatory variable X such th E(u,2) = s2 X;2 . Show how the method of weighted least square regression is superi to OLS in this case.
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Q: Question 5 Let X1 and X2 be random sample of normal distribution with mean 1 and 2 and variance 3…
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Q: QUESTION 5 Which term(s) in the general form of the t statistic is (are) computed differently…
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Q: 1. Derive the least squares estimator of Bo for the regression model Y; = Bo + Ei.
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Q: QUESTION 15 If the least-squares regression line is y = 5 x-3, then for x = 3, the predicted value…
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Q: In estimating the regression in problem #2, you are also concerned that the t-statistics may be…
A: In estimating the regression in problem #2, you are also concerned that the t-statistics may be…
Q: SCENARIO 13-11 A computer software developer would like to use the number of downloads (in…
A: Solution: The estimated least square regression equation is Revenue^= -95.0614+3.7297×Download
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Q: Question 3. For the regression model y, = a + ßx, +ɛ, Show that the least squares normal equations…
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Q: Question 32 Which of the following assumptions is NOT needed for OLS estimators to be unbiased…
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?In a multiple linear regression model with 3 predictor variables, what is the t-statistic for the hypothesis test of the null hypothesis that the coefficient of the second predictor variable is equal to 0, if the estimated coefficient is 0.5, the standard error of the estimate is 0.1, and the degrees of freedom is 15?Consider the simple linear regression model based on normal theory. If we are interested in two different testing H0 : B1 = 0 vs H1: B1 does not = 0 and H0 : p= 0 vs H1: p does not = 0, then show that test statistic value in both the tests are equivalent (values are always same).
- The least-squares regression line relating two statistical variables is given as = 24 + 5x. Compute the residual if the actual (observed) value for y is 38 when x is 2. 4 38 2For the regression model Yi = b0 + eI, derive the least squares estimator.In a typical multiple linear regression model where x1 and x2 are non-random regressors, the expected value of the response variable y given x1 and x2 is denoted by E(y | 2,, X2). Build a multiple linear regression model for E (y | *,, *2) such that the value of E(y | x1, X2) may change as the value of x2 changes but the change in the value of E(y | X1, X2) may differ in the value of x1 . How can such a potential difference be tested and estimated statistically?
- Suppose the simple linear regression model, Yi = β0 + β1 xi + Ei, is used to explain the relationship between x and y. A random sample of n = 12 values for the explanatory variable (x) was selected and the corresponding values of the response variable (y) were observed. A summary of the statistics is presented in the photo attached. Let b1 denote the least squares estimator of the slope coefficient, β1. What is the value of b1?Question 1 Provide an algebraic proof that the least squares estimator is not consistent when Cov(x,e)=0 with the regression model y =B1+B2E(x)+e where E(e)=0 So that E(y) = B1 + B2E(x) Full explain this morning and text typing work only thanksKolmorogov-smirnov test T-test Mann-whitney Linear Regression Are these statistical analyses could be computed in SPSS automatically?
- Question 22: A least squares regression line : A- may be used to predict a value of y if the corresponding x value is given. B- implies a cause-effect relationship between c and y. C- can only be determined if a good linear relationship exists between x and y . D- All of these answers are correct.In Australia, 16% of the adult population is nearsighted.17 If three Australians are chosen at random, what is the probability that two are nearsighted and one is not? 2.state each of the five assumptions of the classical regression model (OLS) and give an intuitive explanation of the meaning and need for each of them.Consider the fitted values from a simple linear regression model with intercept: yˆ = 5 + 6x. Assume that the total number of observations is n = 302. In addition, the R-squared of the regression is R2 = 0.6 and Pn i=1(xi − x¯) 2 = 15, where ¯x is the sample mean of x. Under the classical Gauss-Markov assumptions, a) What is the standard error of the estimated slope coefficient?
