I need help soon as possible II Analytical3. Following the regression output for a data from a random sample of high school seniors in-terviewed in 1980 and re-interviewed in 1986. In this exercise, we use these data to investigatethe relationship between the number of completed years of education for young adults and thedistance from each student's high school to the nearest four-year college. (Proximity to college.lowers the cost of education, so that students who live closer to a four-year college should, onaverage, complete more years of higher education.) Below are the results of a regression of yearsof completed education (ED) on distance to the nearest college (Dist), where Dist is measuredin tens of miles. (For example, Dist = 2 means that the distance is 20 miles.)Dependent Variable: EDSample: 1 3796Method: Least SquaresIncluded observations: 3796VariableStd. ErrorCDISTR-squaredAdjusted R-squaredS.E. of regressionSum squared residLog likelihoodF-statisticCoefficient13.95586 0.037724-0.0733730.013750.007450.0071881.80743812394.36-7632.18228.47582Prob(F-statistic)0(a) Write the regression model using these results.Mean dependent varS.D. dependent varAkaike info criterionSchwarz criterionHannan-Quinn criter.Durbin-Watson stat.t-Statistic369.9451 0-5.3362740(c) Write the mathematical formula for -5.336274Prob.13.829291.8139694.0222244.0255134.0233931.768991(b) Write the mathematical formula for the intercept and the slope and the associated valuesfrom the above estimates.(d) Bob's high school was 20 miles from the nearest college. Predict Bob's years of completededucation using the estimated regression.(e) Does distance to college explain a large fraction of the variance in educational attainmentacross individuals? Explain.

Comments: As per the our company guidelines we are supposed to answer only three subparts. Kindly…

II Analytical 3. Following is the regression output for a data from a random sample of high school seniors in- terviewed in 1980 and re-interviewed in 1986. In this exercise, we use these data to investigate the relationship between the number of completed years of education for young adults and the distance from each student's high school to the nearest four-year college. (Proximity to college lowers the cost of education, so that students who live closer to a four-year college should, on average, complete more years of higher education.) Below are the results of a regression of years of completed education (ED) on distance to the nearest college (Dist), where Dist is measured in tens of miles. (For example, Dist Dependent Variable: ED 2 means that the distance is 20 miles.) Sample: 1 3796 Method: Least Squares Included observations: 3796

II Analytical 3. Following is the regression output for a data from a random sample of high school seniors in- terviewed in 1980 and re-interviewed in 1986. In this exercise, we use these data to investigate the relationship between the number of completed years of education for young adults and the distance from each student's high school to the nearest four-year college. (Proximity to college lowers the cost of education, so that students who live closer to a four-year college should, on average, complete more years of higher education.) Below are the results of a regression of years of completed education (ED) on distance to the nearest college (Dist), where Dist is measured in tens of miles. (For example, Dist Dependent Variable: ED 2 means that the distance is 20 miles.) Sample: 1 3796 Method: Least Squares Included observations: 3796

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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Question

I need help soon as possible

II Analytical
3. Following the regression output for a data from a random sample of high school seniors in-
terviewed in 1980 and re-interviewed in 1986. In this exercise, we use these data to investigate
the relationship between the number of completed years of education for young adults and the
distance from each student's high school to the nearest four-year college. (Proximity to college.
lowers the cost of education, so that students who live closer to a four-year college should, on
average, complete more years of higher education.) Below are the results of a regression of years
of completed education (ED) on distance to the nearest college (Dist), where Dist is measured
in tens of miles. (For example, Dist = 2 means that the distance is 20 miles.)
Dependent Variable: ED
Sample: 1 3796
Method: Least Squares
Included observations: 3796
Variable
Std. Error
C
DIST
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Coefficient
13.95586 0.037724
-0.073373
0.01375
0.00745
0.007188
1.807438
12394.36
-7632.182
28.47582
Prob(F-statistic)
0
(a) Write the regression model using these results.
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat.
t-Statistic
369.9451 0
-5.336274
0
(c) Write the mathematical formula for -5.336274
Prob.
13.82929
1.813969
4.022224
4.025513
4.023393
1.768991
(b) Write the mathematical formula for the intercept and the slope and the associated values
from the above estimates.
(d) Bob's high school was 20 miles from the nearest college. Predict Bob's years of completed
education using the estimated regression.
(e) Does distance to college explain a large fraction of the variance in educational attainment
across individuals? Explain.

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