a. Explanation Calculation: It is given that the simple linear regression is modeled to predict the sweetness index ( y ) from the amount of pectin ( x ) in orange juice manufactured during a production run. From Exercise 11.32, β ^ 1 = − 0.0023 and S S x y = − 130.4417 The following table represent the preliminary calculations. Run Sweetness Index ( y ) Pectin(ppm) ( x ) y 2 1 5.2 220 27.04 2 5.5 227 30.25 3 6.0 259 36.00 4 5.9 210 34.81 5 5.8 224 33.64 6 6.0 215 36.00 7 5.8 231 33.64 8 5.6 268 31.36 9 5.6 239 31.36 10 5.9 212 34.81 11 5.4 410 29.16 12 5.6 256 31.36 13 5.8 306 33.64 14 5.5 259 30.25 15 5.3 284 28.09 16 5.3 383 28.09 17 5.7 271 32.49 18 5.5 264 30.25 19 5.7 227 32.49 20 5.3 263 28.09 21 5.9 232 34.81 22 5.8 220 33.64 23 5.8 246 33.64 24 5.9 241 34.81 ∑ y = 135.8 ∑ x = 6 , 167 ∑ y 2 = 769.72 The value of S S y y is calculated as follows b. To determine Explain the reason for that to give a practical interpretation to s 2 is difficult. c. To determine Derive the range within most of the errors of prediction of sweetness index fall.

13th Edition

ISBN: 9780135820100

Author: MCCLAVE, James T., Sincich, Terry

Publisher: PEARSON

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Chapter 11.3, Problem 50ACI

To determine

Find the values of SSE, s2, and s.

To determine

Explain the reason for that to give a practical interpretation to s2 is difficult.

To determine

Derive the range within most of the errors of prediction of sweetness index fall.

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Chapter 11.3, Problem 49ACI

Chapter 11.3, Problem 51ACI

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Find the values of SSE , s 2 , and s .

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Find the values of SSE, s2, and s.

Explain the reason for that to give a practical interpretation to s2 is difficult.

Derive the range within most of the errors of prediction of sweetness index fall.

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