Suppose that n = 484 i.i.d. observations for (Yj, X¡) yield the following regression results:(= 32.59 + 65.86X, SER= 15.54, R² = 0.74(16.1) (13.3)Another researcher is interested in the same regression, but he makes an error when he enters the data into the regression: He enters each observation twice, so hehas 968 observations (with observation 1 entered twice, observation 2 entered twice, and so forth).Which of the following estimated parameters change as result? (Check all that apply)A.TheR?of the regression.B. The standard error of the regression (SER).C. The estimated intercept and slope.D. The standard errors of the estimated coefficients.Using the 968 observations, what results will be produced by his regression program?( = 32.59 + 65.86X, SER =, R²= 0.74(Round your responses to two decimal places)

The SER measures the spread of the distribution of u. The SER is (almost) the sample standard…

Answered: Suppose that n = 484 i.i.d.…

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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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?).
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and the number of sit-ups a person can do (y). The results were: y = a+bx b = -0.89 a = 23.49 r² = 0.6519 r = -0.8074 a. If a person watches 7 hours of television a day, predict how many sit-ups he can do. b. If a person can do 4 sit ups, predict how many hours of television a day they watch. hours
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.307 b=32.392 r²=0.675684 r=-0.822 Use this to predict the number of situps a person who watches 12.5 hours of TV can do (to one decimal place)
A researcher conducted a number of descriptive statistics for two variables X and Y. They were as follows: SP = 15; SSx = 3; My = 7; Mx = 3 What is b equal to (Please include the sign: e.g., -20)? What is a equal to (please include the sign: e.g., +4.0)? Using b and a construct a regression equation, and then using the regression equation, calculate the value of predicted Y when X = 2?
You’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are: wage = 2.051 + 0.29 × Years of Schooling (0.0802) (0.0168) Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.) The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.284. Interpret the meaning of this value.
A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.
A researcher is interested in finding out the factors which determined the yearly spending on family outings last year (Y, measured in dollars). She compiles data on the number of members in a family (X1), the annual income of the family (X2), and the number of times the family went out on an outing in the last year (X3). She collects data from 196 families and estimates the following regression: Y=120.45+1.54X1+2.12X2+2.12X3. Suppose β1, β2, β3, denote the population slope coefficients of X1, X2, and X3, respectively. The researcher wants to check if neither X1 nor X2 have a significant effect on Y or at least one of them has a significant effect, keeping X3 constant. She calculates the value of the F-statistic for the test with the two restrictions (H0: β1=0, β2=0 vs. H1: β1≠0 and/or β2≠0) to be 3.00. The p-value for the test will be enter your response here?
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.982 b=31.084 r2=0.471969 r=-0.687 Use this to predict the number of situps a person who watches 13.5 hours of TV can do (to one decimal place)
A set of n = 15 pairs of X and Y scores has SSX = 10, SSY = 40, and SP = 30. What is the slope for the regression equation for predicting Y from X? a. 10/30 b. 10/40 c. 40/10 d. 30/10
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.614 b=32.79 r2=0.808201 r=0.899 Use this to predict the final exam score of a student who studies 1 hours per week, and please round your answer to a whole number.

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