Temp. 172 Ratio Temp. 182 Ratio Ratio 0.79 1.38 where S 174 Sxy 1.36 1.67 182 n 175 176 176 177 178 Temp. 184 184 184 186 = - ΣΥ 1.41 182 1.88 1.95 2.63 1.54 βο-ΣΥ-βι Σ×i and B, = Swy = Sxx (Σχ.) (ΣΥ) 1.08 1.00 1.03 0.95 1.66 2.14 n 182 x). 2.49 2.97 1.96 3.03 The equation of the estimated regression line for tank temperature, x, and efficiency ratio, y, is y = Bot Box, where β , is the y-intercept and β, is equal to the slope of the line. The computational formulas for Îo and Î1 are as follows. Π 179 182 183 183 184 186 187 188 1.77 2.06 0.87 1.36 0.99 and Sxx = Ex? - First, let's calculate n, ΣΣΣΣ?, and ΣΥ The sample size is n = 24. The sum of the tank temperatures, Σx; = 4,356. The sum of the efficiency ratios, ΣΥ; =| The sum of the squares of the tank temperatures, Σx = 791,118. The sum of the squares of the efficiency ratios is Σy? = [ The sum of the products of x,y, is Exiyi 190
Temp. 172 Ratio Temp. 182 Ratio Ratio 0.79 1.38 where S 174 Sxy 1.36 1.67 182 n 175 176 176 177 178 Temp. 184 184 184 186 = - ΣΥ 1.41 182 1.88 1.95 2.63 1.54 βο-ΣΥ-βι Σ×i and B, = Swy = Sxx (Σχ.) (ΣΥ) 1.08 1.00 1.03 0.95 1.66 2.14 n 182 x). 2.49 2.97 1.96 3.03 The equation of the estimated regression line for tank temperature, x, and efficiency ratio, y, is y = Bot Box, where β , is the y-intercept and β, is equal to the slope of the line. The computational formulas for Îo and Î1 are as follows. Π 179 182 183 183 184 186 187 188 1.77 2.06 0.87 1.36 0.99 and Sxx = Ex? - First, let's calculate n, ΣΣΣΣ?, and ΣΥ The sample size is n = 24. The sum of the tank temperatures, Σx; = 4,356. The sum of the efficiency ratios, ΣΥ; =| The sum of the squares of the tank temperatures, Σx = 791,118. The sum of the squares of the efficiency ratios is Σy? = [ The sum of the products of x,y, is Exiyi 190
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:Temp. 172
Ratio 0.79 1.38 1.41 1.08 1.00 1.03 0.95 1.77
Temp. 182
Ratio
Temp.
Ratio
174 175 176 176 177 178 179
182
1.36 1.67
1.88
182
1.66 2.14
182
Bo = ΣYi - ¹ ΣXi and ß₁ = Sxy,
n
(Σχ.) (ΣΥ)
where S = =ΣXYi-.
and 5.xx-[x² - ([^;)².
2x -
=
n
n
182
184 184 184 186 186 187 188
2.06
The sum of the squares of the efficiency ratios is
The sum of the products of x,y;, is x,y;=
183
First, let's calculate n, ΣΥΣΣΣ, and ΣΧΥ
The sample size is n = 24.
The sum of the tank temperatures, x, = 4,356.
The sum of the efficiency ratios, y₁=
The sum of the squares of the tank temperatures,
0.87
1.95 2.63 1.54 2.49 2.97 1.96 3.03
183
The equation of the estimated regression line for tank temperature, x, and efficiency ratio, y, is
ý = Bot Bix,
where is the y-intercept and  is equal to the slope of the line. The computational formulas for and ₁ are as follows.
0
1.36
= 791,118.
184
0.99
190
Expert Solution
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Introduction
Regression line is used to predict the value over the another. It used to make the relationship between the independent and dependent variable. The regression coefficients are of two types, they are slope and intercept value. The linear regression equation of the form :
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