Monitoring the yield of a particular chemical reaction at

Chapter 7, Problem 13SE

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QUESTION:

Monitoring the yield of a particular chemical reaction at various reaction vessel temperatures produces the results shown in the following table.

a. Find the least-squares estimates for \(\beta_0\), \(\beta_1\), and \(\sigma^2\) for the simple linear model \(\text {Yield}=\beta_0+\beta_1 \text { Temp}+\varepsilon\).

b. Can you conclude that \(\beta_0\) is not equal to 0?

c. Can you conclude that \(\beta_1\) is not equal to 0?

d. Make a residual plot. Does the linear model seem appropriate?

e. Find a 95% confidence interval for the slope.

f. Find a 95% confidence interval for the mean yield at a temperature of \(225^\circ \mathrm C\).

g. Find a 95% prediction interval for a yield at a temperature of \(225^\circ \mathrm C\).

Equation Transcription:

Text Transcription:

(^oC)

(^oC)

beta_0

beta_1

sigma^2

Yield=beta_0+beta_1 Temp+varepsilon

beta_0

beta_1

225^oC

225^oC

Questions & Answers

QUESTION:

Monitoring the yield of a particular chemical reaction at various reaction vessel temperatures produces the results shown in the following table.

a. Find the least-squares estimates for \(\beta_0\), \(\beta_1\), and \(\sigma^2\) for the simple linear model \(\text {Yield}=\beta_0+\beta_1 \text { Temp}+\varepsilon\).

b. Can you conclude that \(\beta_0\) is not equal to 0?

c. Can you conclude that \(\beta_1\) is not equal to 0?

d. Make a residual plot. Does the linear model seem appropriate?

e. Find a 95% confidence interval for the slope.

f. Find a 95% confidence interval for the mean yield at a temperature of \(225^\circ \mathrm C\).

g. Find a 95% prediction interval for a yield at a temperature of \(225^\circ \mathrm C\).

Equation Transcription:

Text Transcription:

(^oC)

(^oC)

beta_0

beta_1

sigma^2

Yield=beta_0+beta_1 Temp+varepsilon

beta_0

beta_1

225^oC

225^oC

ANSWER:

Step 1 of 7

(a) Let y denote the yield, and let x denote the temperature. Then the least-squares estimates for the model are, 

The estimate of the error variance is the quantity given by

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