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Using any programming language of your choice, develop a function that takes data (x1, y1), ..., (Xn, n), and produces the coefficients ao, a, for linear regression, where the output is y = a, + a,x. Test your function for the table provided in Problem 17.3, and compare the results to your solution to Problem 17.3 (only for y versus x case).

Using any programming language of your choice, develop a function that takes data (x1, y1), ..., (Xn, n), and produces the coefficients ao, a, for linear regression, where the output is y = a, + a,x. Test your function for the table provided in Problem 17.3, and compare the results to your solution to Problem 17.3 (only for y versus x case).

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Using any programming language of your choice, develop a function that takes data (x1, y1), ..., (xn, Yn), and produces the coefficients ao, a, for linear regression, where the output is y = ao + a1x. Test your function for the table provided in Problem 17.3, and compare the results to your solution to Problem 17.3 (only for y versus x case).
Transcribed Image Text:Using any programming language of your choice, develop a function that takes data (x1, y1), ..., (xn, Yn), and produces the coefficients ao, a, for linear regression, where the output is y = ao + a1x. Test your function for the table provided in Problem 17.3, and compare the results to your solution to Problem 17.3 (only for y versus x case).
17.3 Use least-squares regression to fit a straight line to 4 9 11 12 15 17 19 6 8 7 10 12 12 Along with the slope and intercept, compute the standard error of the estimate and the correlation coefficient. Plot the data and the regression line. Then repeat the problem, but regress x versus y- that is, switch the variables. Interpret your results.
Transcribed Image Text:17.3 Use least-squares regression to fit a straight line to 4 9 11 12 15 17 19 6 8 7 10 12 12 Along with the slope and intercept, compute the standard error of the estimate and the correlation coefficient. Plot the data and the regression line. Then repeat the problem, but regress x versus y- that is, switch the variables. Interpret your results.
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