we repeat the data and provide the sample regression equations for Exercises a.Determine the standard error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

Short Answer

Expert verified

The standard error of the estimate is approx 1.732

Step by step solution

01

Part a Step 1 Given Information

02

Part a Step 2 Explanation

From the above Analysis of variance printout,

We haveSSE=6

df=n-2

=5-2

=3

The formula for the standard error of the estimate is given by.

se=SSEn-2

se=SSEn-2

=62

=3

1.732

Hence, The standard error of the estimate is approx 1.732

03

Part b Step 1 Given Information

04

Part b Step 2 Explanation

MINITAB procedure: Step 1: Choose Stat > Regression > Regression.

Step 2: In Response, enter the column Low.

Step 3: In Predictors, enter the columns High.

Step 4: In Graphs, enter the columns High under Residuals versus the variables

Step 5: Click OK.

MINITAB output:

Hence the residuals plot is drawn

05

Part c Step 1 Given Information

06

Part c Step 2 Explanation

MINITAB procedure:

Step 1: Choose Stat > Regression > Regression.

Step 2: In Response, enter the column Low

Step 3: In Predictors, enter the columns High.

Step 4: In Graphs, select Normal probability plot of residuals.

Step 5: Click OK.

MINITAB output:

Hence, the normal probability plot of the residuals is drawn.

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Most popular questions from this chapter

In this Exercise 14.51, we repeat the information from Exercise 14.15.

a. Decide, at the 10%significance level, whether the data provide sufficient evidence to conclude that xis useful for predicting y:

b. Find a 90%confidence interval for the slope of the population regression line.

role="math" localid="1652333468446" x3412y450-1 role="math" localid="1652333507650" y^=-3+x

14.95 Plant Emissions. Following are the data on plant weight and quantity of volatile emissions from Exercise 14.25.

x
57
85
57
65
52
67
62
80
77
53
68
y
8.0
22.0
10.5
22.5
12.0
11.5
7.5
13.0
16.5
21.0
12.0

a. Obtain a point estimate for the mean quantity of volatile emissions of all (Solanum tuberosum) plants that weigh 60g.
b. Find a 95%confidence interval for the mean quantity of volatile emissions of all plants that weigh 60g.
c. Find the predicted quantity of volatile emissions for a plant that weighs 60g.
d. Determine a 95%prediction interval for the quantity of volatile emissions for a plant that weighs 60g.

In Exercises 14.12-14.21, we repeat the data and provide the sample regression equations for Exercises 4.48 -4.57.

a. Determine the standard error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

y^=2.8750.625x

In Exercises 14.48-14.57, we repeat the information from Exercises 14.12-14.21.

a. Decide, at the 10%significance level, whether the data provide sufficient evidence lo conclude that a is useful for predicting y:

b. Find a 90%confidences interval for the slope of the population regression line.

y=1.75+0.25x

1. Suppose that \(x\) and \(y\) are two variables of a population with \(x\) a predictor variable and \(y\) a response variable.

a. The distribution of all possible values of the response variable \(y\) corresponding to a particular value of the predictor variable \(x\) is called a distribution of the response variable.

b. State the four assumptions for regression inferences.

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