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A professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (y) during the same period. The summary data are given as follows: n = 12, * = 4, y = 4 x} = 232, X¡Y = 318, yi = 1025 i=1 Fit a simple linear regression model between x and y by finding out the estimates of the intercept and slope.

A professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (y) during the same period. The summary data are given as follows: n = 12, * = 4, y = 4 x} = 232, X¡Y = 318, yi = 1025 i=1 Fit a simple linear regression model between x and y by finding out the estimates of the intercept and slope.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 25PPS
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IE 7, nd
A professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (v) during the same period. The summary data are given as follows: n = 12, X = 4, y = 4 > x} = 232, ) x¡Y{ = 318, 2 xiyı = 318, > yỉ = 1025 %3D i=1 i=1 i=1 Fit a simple linear regression model between x and y by finding out the estimates of the intercept and slope.
Transcribed Image Text:A professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (v) during the same period. The summary data are given as follows: n = 12, X = 4, y = 4 > x} = 232, ) x¡Y{ = 318, 2 xiyı = 318, > yỉ = 1025 %3D i=1 i=1 i=1 Fit a simple linear regression model between x and y by finding out the estimates of the intercept and slope.
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