C. The standard deviation of fitted values of the dependent variable.D. None of the above.12. According to the Gauss-Markov theorem, when is the OLS estimator said tobe BLUE?A. Another linear unbiased estimator has a smaller variance.B. Any non-linear estimator has a smaller variance.C. No other linear unbiased estimator has a smaller variance.D. None of the above.13. According to the "Law of Large Numbers", if a coin is flipped 1000 times,which of the following statements is true.A. The next flip as has 0.5 chance of being a "head".B. After 1000 flips the proportion of "heads" and "tails" should be similar.C. If 999th flip yields a "head", the 1000th flip should yield a "tail".D. All of the above.14. Why do we prefer the Adjusted R-squared to the R-squared?A. The R-squared is misleading when an insignificant variable is added?B. The R-squared imposes a penalty for any insignificant variable that is added to themodelC. The adjusted R-squared imposes a penalty for adding an insignificant dependentvariableD. None of the above15. Which one is an implication from normal equations?A. The independent variables are not related to the error termB. Regressors are insignificantC. Regressors are significantD. None of the aboveSECTION B: Answer ALL questionsQn1. Consider a Linear Regression Model Y₁ = Bo+₁x₁+₁ and the following dataentriesObservation Talk time consumption Monthly IncomeConstant112843121204811355614361341 4. Which of the following is used in model fit comparisons?A. Alkaike Information Criterion testB. The R-squared adjustedC. The Bayesian Information CriterionD. All of the above5. Dr. Musantu conducted an estimation between y (dependent variable) and x(independent variable) in Stata. He obtained 0.332 coefficient of x and standarderror of 0.021. What is the value of the t-statistic?A. 14.80901392B. 15.809C. 16.809D. None of the above6. Is the above regressor (in question 8) significant at 5% (which gives 1.96critical values) level of significance?A. NoB. Yes7. In a log-log regression model, what does the slope coefficient measure?A. The elasticity or percentage change of y with respect to a percentage change in x.B. The change in y which the model predicts for a unit change in x.C. The change in x which the model predicts for a unit change in y.D. 100 multiplied by the ratio y/x.0.021

“Since you have asked multiple questions, we will solve the first question for you. If you want any…

Answered: C. The standard deviation of fitted…

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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B.13. Table B-6 gives data on the number of new business incorporations (Y) and the number of business failures (X) for the United States from 1984 to 1995. a. What is the average value of new business incorporations?And the variance? b. What is the average value of business failures? And the variance? c. What is the covariance between Y and X? And the correlation coefficient? (X) + var (Y) sr= -0.8 (X+Y) 2X = 16, s2Y = 9Y = 3X2 + 2Y = ax + bY = X>4Y = 0.6X-4 Y = 3X +2 E(X) = 8 and var (X) = 4 E(XY) = a 4X=1 a 2 Y = 1 XIYi f(XI, YI) X = 20 NUMBER OF NEW BUSINESS INCORPORATIONS (Y) AND NUMBER OF BUSINESS FAILURES (X), UNITED STATES, 1984-1995 YEAR Y X 1984 634,991 52,078 1985 664,235 57,253 1986 702, 738 61,616 1987 685,572 61, 111 1988 685,095 57,097 1989 676,565 Source: Economic Report of the President, 2004, Table B-96, p. 395. TABLE B-6 d. Are the two variables independent? e. If there is correlation between the two variables, does this mean that one variable causes the other…
Which statement is not correct?A. Spurious correlation can often be reduced by expressing X and Y in per capita terms.B. Autocorrelation is mainly a concern if we are using time - series data.C. Heteroscedastic residuals will have roughly the same variance for any value of X.D. Standardized residuals make it easy to identify outliers or instances of poor fit. ( don't hand writing solution)
Two coworkers commute from the same building. They are interested in whether or not there is any variation in the time it takes them to drive to work. They each record their times for 20 commutes. The first worker's times have a variance of 12.2. The second worker's times have a variance of 16.9. The first worker thinks that he is more consistent with his commute times and that his commute time is shorter. Test the claim at the 10% level.What is the F statistic? (Round your answer to two decimal places.)
Answer last 3 parts. t hank y o u.
Incorrect. The weight of boxes of candy is a normal random variable with mean and variance 1/10 pound2. The prior distribution for u is normal with mean 5.01 pound, and variance 1/25 pound2. A random sample of 9 boxes gives a sample mean of x = 5.02 pound. Find the Bayes estimate of u. Round your answer to three decimal places. ji i 5.015
Compute mean, variance, and standard deviation
Fresh Mart QQ's profit on each delivery is estimated by RM P, where the random variable P has mean u and variance 1.92. According to previous record, the value of u used to be 0.85. Manager suspects that this value has increased. In order to test at the 5% significance level whether the value of u has increased, a random sample of 50 delivery transaction is chosen. Assume the variance of P is unchanged. Given that Ep 59. Find the unbiased estimates of the population mean. Stating the null and alternative hypotheses, test at 5% significance level on whether the manager's suspicion is true. The alternative hypothesis for a test is stated as below: H:µ # 30 State the null hypothesis and determine whether this test is one-tail test or two- tail test hypothesis.
13. STATEMENTS FIRST: CORRELATION CAN BE USED TO DETERMINE THE DEGREE OF RELATIONSHIP BETWEEN VARIABLES SECOND: COEFFICIENT CORRELATION RANGES FROM 0-1A. IF BOTH STATEMENTS ARE TRUEB. IF BOTH STATEMENTS ARE FALSEC. IF THE FIRST IS TRUE AND THE SECOND IS FALSED. IF THE FIRST IS FALSE AND THE SECOND IS TRUE 14. STATEMENTS FIRST; STANDARD DEVIATION IS THE SQUARE ROOT OF THE VARIANCE SECOND: DISPERSION GIVES US THE IDEA OF THE DEGREE OF SCATTERING OF THE DATA IN THE DISTRIBUTION A. IF BOTH STATEMENTS ARE TRUEB. IF BOTH STATEMENTS ARE FALSEC. IF THE FIRST IS TRUE AND THE SECOND IS FALSED. IF THE FIRST IS FALSE AND THE SECOND IS TRUE 15. CHARACTERISTICS OF THE NORMAL CURVEI. CURVE IS ASYMMETRICAL ABOUT MEANII. TAILS OF THE NORMAL CURVE ARE ASYMPTOTIC RELATIVE TO THE HORIZONTAL LINEIII. TOTAL AREA UNDER THE NORMAL CURVE IS EQUAL TO 1IV. NORMAL CURVE ARE SUBDIVIDED INTO THE THREE STANDARD DEVIATION A. I, II, AND III ONLYB. II, III, AND IV ONLYC. I, II, III, AND IVD. I, II, AND IV ONLYE. I,…
You may need to use the appropriate technology to answer this question. The following data are from a completely randomized design. In the following calculations, use a = 0.05. Treatment Treatment Treatment 3 64 82 69 47 71 53 54 87 60 35 64 46 50 76 57 148.67 108.67 96.67 (a) Use analysis of variance to test for a significant difference among the means of the three treatments.
Consider a regression analysis with n= 51 and four potential independent variables. Suppose that one of the independent variables has a correlation of 0.49 with the dependent variable. Does this imply that this independent variable will have a very small Student's t statistic in the regression analysis with all four predictor variables? Choose all that apply. A. The correlation between the independent variable and the dependent variable could result in a very small Student's t statistic as the correlation creates a high variance. B. Correlation between the independent variable and the dependent variable is not necessarily evidence of a small Student's t statistic. C. A high correlation among the independent variables could result in a very small Student's t statistic as the correlation increases the coefficient standard errors. D. Correlation between the independent variable and the dependent variable is evidence of a small Student's t statistic.
LINEAR REGRESSION 1) An important company asks you as a professional to build a report where the products are evidenced defective ( x ) versus the number of times maintenance and supervision was performed on the machine ( y ) and they supply these data. (img 1) A. What are the mean and median of each distribution? B. What is the variance and standard deviation of each distribution? C. Make the scatterplot, calculate the covariance and discuss it D. Calculate Pearson's correlation coefficient. Is it consistent with covariance? comment on it thanks for help
d and e please

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