Suppose the equation estimated using data is:log(rent) = .043 + .066 log(pop) + 507 log(avginc) + .0056 pctstu(.081)(.844) (.039)(.0017)n = 64, R² = .458.We would like to test the hypothesis that size of the student body relative to thepopulation has no ceteris paribus effect on monthly rents.Can you reject the hypothesis against the two-sided alternative at the 5% levels?OYes because the t statistics is above the critical value. We can reject thehypothesis HO: beta3=0.Yes because the t statistics is below the critical value. We can reject thehypothesis HO: beta3 =0.No because the tstatistics is above the critical value. We cannot reject thehypothesis HO: beta3 =0.No because the t statistics is below the critical value. We cannot reject thehypothesis HO: beta3 =0.Question 8Using the standard normal approximation, find the 95% confidence interval forbeta3.The lower bound = Blank 1The upper bound = Blank 2Round off your answer up to 3 decimal places. (If 0.01 is the answer, you can answereither 0.01, 0.010, .01, or .010.Blank # 1Blank # 2 Question 5Suppose that the causal population regression model (the true model) is given by.where y is the wage, x] is the individual's education (years of education), x2 is the individual's on-the-job training,and x3 is the individual's ability.Suppose that we know the true population parameters are given as:Bo = 15, B1= 0.2, 2= 0.1, 53= 1.0You do not observe ability and run the following regression model:y = bo+ bjx+ bgx +e (2)where bo, b1 , and b, are parameters and e is the error term. As we already discussed, the error term e inEquation (2) includes B3%3+ *.Suppose you got three observations (for illustration purpose, assume that this is the population data; i.e.you are only interested in these three individuals.).Years of Education (X1)Wage (Y)On-the-job Training (X2)Error Term (e)15153010.5102010-920104020What is the sign of the bias in the estimate of 6, if you run regression without x3 ? [Blank 1]What is the sign of the bias in the estimate of ß, if you run regression without x3 ? [Blank 2]Note: Give an answer either positive or negative.Blank # 1Blank # 2

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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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Suppose a data set of 200 observations (n = 200) was analyzed using OLS to examine the relationship between CEO salary and various measures of firm performance. The regression results are as follows, with standard errors in parentheses: logy = 5 + 0.2logx₁0.03x₂ +0.002x3 (0.2) (0.04) (0.004) where? (0.009) y = CEO salary in thousands of dollars X₁ = annual firm sales X₂ = percentage of sales lost to competitors X3 = return on stock in percent R² = 0.290 Suppose you want to test the null hypothesis that percentage of sales lost to competitors has no ceteris paribus effect on the salaries of CEOS. For the one-sided alternative hypothesis ß₂ < 0 and 1% rejection rule (i.e., at the 1% level), you would_ the null hypothesis that ß₂ = 0.
pan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. An article reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). The following data was read from a graph in the article. x 125.8 98.1 201.4 147.3 145.9 124.7 112.2 120.2 161.2 178.9 159.5 145.8 75.1 151.5 144.2 125.0 198.8 133.9 y 77.9 76.8 81.5 79.8 78.2 78.3 77.5 77.0 80.1 80.2 79.9 79.0 76.9 78.2 79.5 78.1 81.5 71.0 (a) Determine the slope and intercept of the estimated regression line. (Round your answers to 5 decimal places, if needed.)slope: intercept: (b) Does there appear to be a useful linear relationship? Carry out a test using the ANOVA approach and a significance level of 0.05. State the appropriate null and alternative hypotheses.…
Reliability testing of the new 2.0 liter Chevy automotive engine has resulted in a time to failure distribution which is lognormal with = 90,000 mi. and s = 0.60. Find: med %3D a. R(40,000 mi.) b. MTTF and Std. Dev. c. R(90,000|40,000) d. t .90
Suppose u1 and uz are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 6, x = 115.6, s1 = 5.03, n = 6, y = 129.9, and s2 = 5.38. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) In USE SALT Does the interval suggest that precise information about the value of this difference is available? Because the interval is so narrow, it appears that precise information is available. Because the interval is so narrow, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is not available. o Because the interval is so wide, it appears that precise information is available.
Suppose the relationship between Y and X is given by: Y = 50 + 3X + error By how much does the expected value of Y change if X decreases by 2 units?
For a MR model with 4 predictors, we have: SSE 288 and SST = 957 What percentage of the variation in Y is accounted for by its assumed relationship with the predictors?
For healthy adults, the mean pH level is µ = 7.4, a new drug for arthritis has been developed. However, it is thought that this drug may change blood pH. A random sample of 33 patients with arthritis took the drug for three months. Blood tests showed that the sample mean from these 33 patients was a pH of 8.0 and it is known that o = 2.3. (Note, there is no unit for this type of data). Use a = 0.05 level of significance to test the claim that the drug has increased the mean pH level of the blood. If we use the classical approach, what would the criterion (step 3) be? O -1.645 or less O -2.33 or less 1.645 or more O 2.33 or more
Suppose the relationship between Y and X is given by: Y = 25 - 3X + error By how much does the expected value of Y change if X decreases by 1 unit?
What happened to the standard error of educ after adding KWW to the model? Discuss. Do you agree or disagree with the following statement? “If the log of the dependent variable appears in the regression, changing the unit of measurement of any independent variable affects both the slope and intercept coefficients”. Discuss by providing the resource.
Suppose the relationship between Y and X is given by: Y = 25 - 3X + error By how much does the expected value of Y change if X decreases by 2 units?
If you have a b of 0.56 in a regression equation, what does this mean? For every one-unit increase in x, you get an increase of 0.56 in y r = .31 On average, the variability of real scores around the regression line is 0.56 For every 1 standard deviation increase in x, you get an increase of 0.56 standard deviations in y
An investigation into the relationship between an adolescent mother's age x in years and the birth weight y of her baby in grams yielded the regression equation y= - 1163.45 + 245.15x as well as r = .88369, r2= .78091, SSE = 337212.45, and s= 205.30844 1) What is the predicted birth weight for a baby brn to a 17 year old woman? 2) What is the propotion of the variability in the weights of babies born to adolescent mothers that is accounted for by the mother's age? 3) For every additional year in the mother's age that mean birth weight of the baby? (a) increases by about 245g (b) decreases by about 245g (c) increases by about 1163g (d) increases by about 1163g (e) changes by an amount that cannot be determined from the information given.

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