In a study of the relationship between real aggregate consumption and pricesin a specific country based on a time series of 104 observations, the followingOLS regression function was obtained (standard errors in parentheses),C; = 13.74 + 0.24P,(0.35)R = 0.12,SER= 2.85,(1)(0.05)where C, is logarithm of consumption and P, is logarithm of price.(a) Is the coefficient on P statistically significant?(b) Compute the p-value for the test of significance of the coefficient on P.(c) Comment on the sign of the coefficient on P.

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Answered: In a study of the relationship between…

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 sample regressions for the linear and the logarithmic models. Linear Logarithmic Intercept 6.7904 −5.6712 x 1.0607 NA In(x) NA 10.5447 * se 2.4935 1.5231 R2 0.8233 0.9341 Adjusted R2 0.8013 0.9259 b. Use the selected model to predict y for x = 10. (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) predicted y=
Consider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. What is the subpopulation mean when x = 7 servings per day?
A regression of average monthly expenditure (AME, measured in euros) on average monthly income (AMI, measured in euros) using a random sample of college-educated full-time workers earnings €100 to €1.5 million yields the following: AME = 710.7 + 8.8 × AMI, R2 = 0.030, SER = 540.30 d. What does the regression predict will be the expenditure of a person with an income of €100? With an income of €200? e. Will the regression give reliable predictions for a person with an income of €2 million? Why or why not? ( f. Given what you know about the distribution of earnings, do you think it is plausible that the distribution of errors in the regression is normal? (Hint: Do you think that the distribution is symmetric or skewed? What is the smallest value of earnings, and is it consistent with a normal distribution?).
To determine characteristics associated with Y = whether a cancer patient achieved remission (1 = yes), a study used logistic regression. The most important explanatory variable was a labeling index (LI) that measures proliferative activity of cells after a patient receives an injection of tritiated thymidine. It represents the percentage of cells that are “labeled.” Table 4.8 shows the grouped data. Software reports Table 4.9 for a logistic regression model using LI to predict π = P (Y = 1). A. Show how software obtained π ̂ = 0.068 when LI = 8. B. Show that π ̂ = 0.50 when LI = 26.0 D. The lower quartile and upper quartile for LI are 14 and 28. Show that π ̂ increases by 0.42, from 0.15 to 0.57, between those values. E. When LI increases by 1, show the estimated odds of remission multiply by 1.16
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
Take a look at the following sample regressions (type of regression in top row), choose the type of model that best fits the data. Linear Logarithmic Intercept 6.7904 −5.6712 x 1.0607 NA In(x) NA 10.5447 se 2.4935 1.5231 R2 0.8233 0.9341 Adjusted R2 0.8013 0.9259 Linear Logrithmic Both equally Neither model explains a majority of the variation in y
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3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
Interpret the coefficient estimate on Married in column 2, commenting on both magnitude and statistical significance
Consider the following OLS regression results, In(inc)=1.970+.083educ, R²=.186, where inc represents annual income (in $1000s) and educ represents years of education. The slope estimate on years of education can be interpreted as an additional year of education is associated with an .083% increase in income. an additional year of education is associated with an 8.3% increase in income. a 1% increase in education is associated with an increase in income of $83. a 1% increase in education is associated with an increase in income of $8,300.
lakhs) of a certain commodity for the year On the basis of quarterly sales (in 2008-12, the following calculations were made : Trend: Y = 20 + 0.5 t with origin at 1st quarter of 2008. where 1 = time unit = one quarter and y = quarterly sales ( Seasonal variations: Quarter I II III IV Seasonal Index 80 90 120 110 Estimate the quarterly sale for the year 1979 using multiplicative model.
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,160.10 +3147.75(Education) + 1230.34(Experience) Suppose an employee with 8 years of education has been with the company for 20 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? Answer Tables Keypad Keyboard Shortcuts

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