1. Consider the normal linear regression model Y~ N(a + Bx, o²). Data pairs (xi, yi) of sample size n= 43 have been collected and summarised below: n n n n n Σ |xi = 11.3, Σw = 154.8, Σy = 19.2, Σy =135, & Σαϊy = 24.9. i=1 i=1 i=1 i=1 i=1 From this data, compute the least-squares estimates for a and ß. Given that the residual variance estimate is s² = 0.0544, evaluate the expected value and 95% prediction interval a future response Yo at x = 10. Clearly state the definitions/formulas you are using in this question and report the pre- dicted value and interval correct to 2 decimal places. From the given information, provide a brief comment about this prediction.
1. Consider the normal linear regression model Y~ N(a + Bx, o²). Data pairs (xi, yi) of sample size n= 43 have been collected and summarised below: n n n n n Σ |xi = 11.3, Σw = 154.8, Σy = 19.2, Σy =135, & Σαϊy = 24.9. i=1 i=1 i=1 i=1 i=1 From this data, compute the least-squares estimates for a and ß. Given that the residual variance estimate is s² = 0.0544, evaluate the expected value and 95% prediction interval a future response Yo at x = 10. Clearly state the definitions/formulas you are using in this question and report the pre- dicted value and interval correct to 2 decimal places. From the given information, provide a brief comment about this prediction.
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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I'm sorry to bother, but it's hard for me to read the answer you give. Could you rewrite the calculations in math equations(Latex maybe)? Hand-written will be great as well.
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