In a study of the determinants of household expenditures on vacation travel, data were obtained from a sample of 2226 households. The model estimated isshown below, with R² = 0.187. The numbers in parentheses under the coefficients are the estimated coefficient standard errors. Complete parts a through d.log y = - 4.061 + 1.1532 log x₁ -0.4416 log x₂y = expenditure on vacation travel= total annual consumption expenditureX1X₂ = number of members in household(0.0527)(0.0453)Click the icon to view a table of critical values for the Student's t-distribution.a. Interpret the estimated regression coefficients.All else being equal, a 1% increase in annual consumption expenditures will be associated with aelse being equal, a 1% increase in the size of household will be associated with a %%in expenditures on vacation travel.in expenditures on vacation travel. All

The regression equation is, log y = –4.061 + 1.1532 log x1 – 0.4416 log x2, where y defines the…

Answered: In a study of the determinants of…

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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Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 11,433.70 + 3312.68(Education) + 819.54 (Experience ) Suppose an employee with 7 years of education has been with the company for 5 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? 囲 Tables E Keypad Answer Keyboard Shortcuts
(Medicare). The annual expenditures for Medicare (in billions of dollars) by the US Government for selected years since 1980 are shown in Table 4. Let x represent the years since 1980. (Use 4 decimal places in all answers.) Table 4: Medicare Expenditures Year Billion $ 1980 37 1985 72 1990 111 1995 181 2000 197 2005 330 A. Find the exponential regression model for the data.M(x) = B. What is the r2 value for this model?r2 = C. Extimate (to the nearest billion) the expenditures in 2008?The Medicare expenditures in 2008 were about $ billion.
Question: Give the equation of the model you chose in (b ) using the transformed variables .
Table 4.18 shows estimated effects for a fitted logistic regression model with squamous cell esophageal cancer (1 = yes, 0 = no) as the response variable Y. Smoking status (S) equals 1 for at least one pack per day and 0 other- wise, alcohol consumption (A) equals the average number of alcoholic drinks consumed per day, and race (R) equals 1 for blacks and 0 for whites. A. To describe the race-by-smoking interaction, construct the prediction equation when R = 1 and again when R = 0. Find the fitted YS conditional odds ratio for each case. Similarly, construct the prediction equation when S = 1 and again when S = 0. Find the fitted YR conditional odds ratio for each case. Note that, for each association, the coefficient of the cross-product term is the difference between the log odds ratios at the two fixed levels for the other variable. B. In Table 4.18, explain what the coefficients of R and S represent, for the coding as given above. What hypotheses do the P -values refer to for…
Hanny
Comment on the statistical significance of the estimated logit model.
Consider the following model, known as the exponential regression model: Y; = BoefiXi + ui Do you think that you can estimate the model parameters using OLS? Explain. What do you suggest how to estimate the model parameters? How do you think one can proceed estimating these by trial-and-error, or iterative, process?
Can gender, educational level, and age predict the odds that someone votes for a particular candidate in the election? Over 1500 voters were selected, and data were col-lected on the highest year of school completed, their age, and their gender. We wish to t a logistic regression model: log(1 p p ) = 0 + 1Age + 2Education + 3Gender, where p is the binomial probability that a person voted for candidate Johnson, and gender is coded as the indicator for female. The R output is given below. parameter df estimate s.e z p-value (Intercept) 1 .1119 .3481 .321 .748 Age 1 .0020 .0032 .613 .54 Education 1 -.0100 .0184 .547 .585 Gender 1 .4282 .1040 4.117 .000 Null deviance: 255.95 on 1499 degrees of freedom Residual deviance: 220.80 on 1496 degrees of freedom Write down the tted logistic regression and give a short summary about the data analysis . Calculate the probability of voting for Johnson for a…
QUESTION 7 In order to estimate the effect on wage of years of schooling, researcher B analysed the dataset that researcher A collected in the previous question. Researcher B considers the following regression equation, log(income);=Bo+Bieduc;+ + u; %3D where educ, is years of school of individual j and she realised that unobserved factors such as motivation, and work ethic, would determine the income level and be correlated with the variable of interest i ... includes additional terms associated with other characteristics in the data set. When researcher B was carefully examining omitted factors in the error term Up regarding the unobserved factors is correct, then: educ; If researcher B's conjecture O a. The OLS estimator a would not be computed. Ob. The OLS estimator B1 would overestimate the effect on income, of educ; c. The OLS estimator B1 would would suffer imperfect multicollinearity. Od. The OLS estimator B1 would have a large standard error. Oe. The OLS estimator B1 would…
The following data gives the approximate population of the world for selected years from 1850 until2000. Year 1850 1900 1950 1980 2000 Population 1.3 (billions) 1.6 3 4.4 Assume that the population growth can be modeled with an exponential function p = bemx where x is the year and p is the population in billions. Use linearleast-squares regression to determine the constants b and m for which the function best fits the data. Use the equation to estimate the population in the year 1970.
Consider the logit regression log(odds(QualExam) = ßo + B, • ParEduc + B, • Awards. where QualExam is a binary variable that indicates passing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicates having experience of obtaining award(s) if equal to 1, and not having experience if 0. Given the parents' average education level unchanged, the odds ratio is expected to be _ for an individual with awards to pass the exam comparing to those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam is approximately_. ParEduc Awards Intercept -10.53 2.98 0.48 O A. 0.48; 80%. O B. 1.616; 80%. O C. 1.616; 4%. O D. 0.48; 4%.
Would you include ros in a final model explaining CEO compensation in terms of firm performance?

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