5. Given the data Y, = 10, Y, = 9, and Y = 9.5, we wish to fit an IMA(1,1) model without a constant term. (a) Find the conditional least squares estimate of 0. (Hint: Do Exercise 4 first.) (b) Estimate a?.
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- Show what correction (using the generalized least squares method) we should use if the form of heteroskedasticity was the following, show mathematically For both a) and b)When a least squares line is fit to the 12 observations in the labor cost data, we obtain SSE =656, 214.3589. Calculate s2 and s (isnt n-k-1)?In Galton’s height data (Figure 7.1, in Section 7.1), the least-squares line for predictingforearm length (y) from height (x) is y = −0.2967 + 0.2738x.a) Predict the forearm length of a man whose height is 70 in.b) How tall must a man be so that we would predict his forearm length to be 19 in.?c) All the men in a certain group have heights greater than the height computed in part(b). Can you conclude that all their forearms will be at least 19 in. long? Explain.
- 1) Assuming you have a data matrix X that has n rows and p variables and you know both µ and Σ. How is (X- µ)‘Σ-1(X- µ) distributed? 2) Assuming that you don’t know the values of µ and Σ. How is the statistical distance distributed as n-p gets large?4) Here are data on the lengths of male and female roaches (in mm). Your job is to find out if there is adifference between male and female roaches (this should be two sided - why?).males 15.4 13.9 12.7 9.6 6.6 10.7 9.9 13.3 16.2 9.0 11.4 16.6 12.2females 16.7 16.3 12.8 16.9 15.1 12.8 18.7 18.3 8.6 13.6 15.3 16.2 13.4It's up to you to figure out what the best procedure is, what kind of hypotheses to use, which α to use,what test to use, and so on. Make sure you follow all the appropriate steps. You should probably use Ras you’ll get done much quicker. Remember to very clearly state your results in writing. Never turn in just an R printout .Hint: how do you decide which test to use? What kind of distributions do the data have?The following are the scores that 12 students obtainedon the midterm and final examinations in a course instatistics:Midterm examination Final examinationx y71 8349 6280 7673 7793 8985 7458 4882 7864 7632 5187 7380 89 (a) Find the equation of the least squares line that willenable us to predict a student’s final examination score inthis course on the basis of his or her score on the midtermexamination.(b) Predict the final examination score of a student whoreceived an 84 on the midterm examination.
- Consider the fitted values from a simple linear regression model with intercept: yˆ = 7 + 4x. Assume that the total number of observations is n = 20. In addition, the explained sum of squares is SSE = 10 and the residual sum of squares is SSR = 30. Under the classical Gauss-Markov assumptions, a) What is the value of the R2 ?A producer of pocket calculators purchases the main processor chips in lots of1,000. The producer would like to have a 1 percent rate of defectives but willnormally not refuse a lot unless it has 4 percent or more defectives. Samples of50 are drawn from each lot, and the lot is rejected if more than two defectives arefound.b. Compute A and B Use the Poisson approximation for your calculations32-Which of the following is the z function in terms of the variable u that needs to be converted to fit the power function in the form of y=a.x^b to the points given by the least squares method?
- Texas Instruments produces computer chips in production runs of 1 million at a time. It has found that the fraction of defective modules can be very different in different production runs. These differences are caused by small variations in the set-up of each production run. Managers have observed that defective rates are roughly triangular, with a lower bound of 0%, and an upper bound of 50%. Defects more likely to be near 10% than any other single value in their range. Now suppose that we have taken a sample of 10 modules, and 2 of them are defective. i. What is the conditional probability of a defective rate less than 25% in this production run?ii. For what number M would you say that the defective rate is equally likely to be above or below M?b) What are the three models proposed as extensions of the GARCH model? Describe their advantages over the GARCH.What are the difficulties in estimating the following model? Use as much detail as possible in answering this question while considering the Gauss-Markov assumptions and OLS estimator. Economic productivity = β0 + β1Unemployment + β2Innovation + θiControls + ei Where unemployment is the average unemployment rate of a country and innovation is an index of R&D performance.