Ans 4 & 5 PROBLEMS1. Fit the following data in a linearly regressed line. Find the standard deviation.0.10.20.30.50.70.160.320.560.842.02. Fit the following data in a linear regression line. Find the standard error of estimate.0.41, si, 10-3 Al0.2 0.3683 0.3819 0.2282 0.0486 0.0082 0.14410.20.40.60.81.23. Using the following data by linear interpolation, find the temperature at y = 2 cm.35у, стT, K9004802702004. Fit the following data in a second order linear interpolation polynomial.3Y, cmT, K9004802705. Fit the following data in a linearly regressed line. Find the co-efficient of variation.X, cm2457 101, mm21.351.341.61.581.42Page 1 of 1

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4. Fit the following data in a second order linear interpolation polynomial. 3 У, ст 1 T, K 900 480 270

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

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Question

Ans 4 & 5

PROBLEMS
1. Fit the following data in a linearly regressed line. Find the standard deviation.
0.1
0.2
0.3
0.5
0.7
0.16
0.32
0.56
0.84
2.0
2. Fit the following data in a linear regression line. Find the standard error of estimate.
0.4
1, s
i, 10-3 Al0.2 0.3683 0.3819 0.2282 0.0486 0.0082 0.1441
0.2
0.4
0.6
0.8
1.2
3. Using the following data by linear interpolation, find the temperature at y = 2 cm.
3
5
у, ст
T, K
900
480
270
200
4. Fit the following data in a second order linear interpolation polynomial.
3
Y, cm
T, K
900
480
270
5. Fit the following data in a linearly regressed line. Find the co-efficient of variation.
X, cm
2
4
5
7 10
1, mm
2
1.35
1.34
1.6
1.58
1.42
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