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Qn1. Consider a Linear Regression Model Y₁ = Be + B₁x₁ +E; and the following data entries Observation Talk time consumption Monthly income Constant 1 128 43 1 2 120 48 2 125 56 1 1

Qn1. Consider a Linear Regression Model Y₁ = Be + B₁x₁ +E; and the following data entries Observation Talk time consumption Monthly income Constant 1 128 43 1 2 120 48 2 125 56 1 1

MATLAB: An Introduction with Applications
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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Linear regression

Qn1. Consider a Linear Regression Model Y₁ = Be + Pix, + &; and the following data entries 4 Observation Talk time consumptic Monthly income Constant 1 128 43 1 120 48 1 135 56 1 143 61 1 141 67 1 152 70 1 a) Derive the Ordinary Least Squares (OLS) estimator of B1 and Bo- b) Using information in the table above, calculate the values of the estimates in (a) Write down the fitted/predicted model d) Given that the above model (y; = Bo + B₁x; + E₁) is a log-log model of 'Taik time consumption' (regressand) and 'monthly income' (regressor). How would you interpret the estimates of Bo and B₁? Using the information from the table and results from above questions, calculate and interpret the R-squared 23456
Transcribed Image Text:Qn1. Consider a Linear Regression Model Y₁ = Be + Pix, + &; and the following data entries 4 Observation Talk time consumptic Monthly income Constant 1 128 43 1 120 48 1 135 56 1 143 61 1 141 67 1 152 70 1 a) Derive the Ordinary Least Squares (OLS) estimator of B1 and Bo- b) Using information in the table above, calculate the values of the estimates in (a) Write down the fitted/predicted model d) Given that the above model (y; = Bo + B₁x; + E₁) is a log-log model of 'Taik time consumption' (regressand) and 'monthly income' (regressor). How would you interpret the estimates of Bo and B₁? Using the information from the table and results from above questions, calculate and interpret the R-squared 23456
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