6. (a) Suppose that n = 100 i.i.d observations for (Y, X,) yield the following results where SER standsfor the standard error of the regression:Ý32.1+66.8X, SER=15.1, R2 = 0.81(15.1) (12.2)Another researcher is interested in the same regression, but he makes an error when he enters thedata into his regression program: He enters each observation twice, so he has 200 observations.Using these 200 observations, what results will be produced by his program? Write it in thefollowing format:=9+X, SER=(b) Suppose that a random sample of 200 twenty-year-old-men is selected from a population and thatthese mens height and weight are recorded. A regression of weight on height yields Weight-99.41 +3.94 x Height. Suppose further that instead of measuring weight and height in poundsand inches, these variables are measured in centimeters and kilograms. What are the regressionestimates from this new centimeter-kilogram regression? (1 inch= 2.54 cm, 1 pound=0.45 kg)=

The regression equation is given as follows. Y = 32.1 + 66.8X SER = 15.1R2 = 0.81n =100

6. (a) Suppose that n 100 i.i.d observations for (Y., X.) yield the following results where SER stands for the standard error of the regression: Ŷ 32.1+66.8X, SER=15.1, R20.81 (15.1) (12.2) Another researcher is interested in the same regression, but he makes an error when he enters the data into his regression program: He enters each observation twice, so he has 200 observations. Using these 200 observations, what results will be produced by his program? Write it in the following format: O 9+X, SER= ,R² (-) (-) (b) Suppose that a random sample of 200 twenty-year-old-men is selected from a population and that these mens height and weight are recorded. A regression of weight on height yields Weight -99.41 +3.94 x Height. Suppose further that instead of measuring weight and height in pounds. and inches, these variables are measured in centimeters and kilograms. What are the regression estimates from this new centimeter-kilogram regression? (1 inch 2.54 cm, 1 pound-0.45 kg)

6. (a) Suppose that n 100 i.i.d observations for (Y., X.) yield the following results where SER stands for the standard error of the regression: Ŷ 32.1+66.8X, SER=15.1, R20.81 (15.1) (12.2) Another researcher is interested in the same regression, but he makes an error when he enters the data into his regression program: He enters each observation twice, so he has 200 observations. Using these 200 observations, what results will be produced by his program? Write it in the following format: O 9+X, SER= ,R² (-) (-) (b) Suppose that a random sample of 200 twenty-year-old-men is selected from a population and that these mens height and weight are recorded. A regression of weight on height yields Weight -99.41 +3.94 x Height. Suppose further that instead of measuring weight and height in pounds. and inches, these variables are measured in centimeters and kilograms. What are the regression estimates from this new centimeter-kilogram regression? (1 inch 2.54 cm, 1 pound-0.45 kg)

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Consider the regression model Yi=bot Bi Xitui Suppose that you know Bo = 0. Derive the formula for the least squares estimator of B₁. The least squares objective function is O A. n O B. O C. O D. E (Yi-bo-b1Xi) i=1 n Σ (Yi-bo-biXi) i=1 2 n Σ (v₁²-bo-b₁x₁²) i=1 n E (Yi-bo-b+Xi) 3 i=1
Table 4.1 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.99794806 Missing 0.99513164 Standard Error 1.64839211 Observations 20 ANOVA Significance F af Missing 16 19 MS F Regression 10561.07486 Missing 1295.585 2.66E-19 Residual 43.47514498 2.717197 Total 10604.55 Coefficients 0.562 Standard Error t Stat P-Value Intercept X1 1.327 0.424 0.677 0.959 0.038 25.245 0.000 X2 1.117 0.125 8.916 0.000 X3 1.460 0.066 22.185 0.000 Consider the output shown in Table 4.1. Which of the predictors has the greatest impact on the dependent variable? X2 Intercept X1 X3
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