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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

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

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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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 Page 1 of 1
Transcribed Image Text: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 Page 1 of 1
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