The Information Please Almanac provides data on the ages at inauguration and of death for the presidents of the United States. We give those data on the WeissStats site for those presidents who are not still living at the time of this writing.

a. obtain and interpret the standard error of the estimate.

b. obtain a residual plot and a normal probability plot of the residuals.

c. decide whether you can reasonably consider Assumptions \(1-3\) for regression inferences met by the two variables under considerations.

Short Answer

Expert verified

Part a. From the MINITAB output, the standard error of the estimate is \(9.705\).

Part b. The residual plot and normal probability plot are obtained.

Part c. The assumptions for the regression inferences are not violated for the variables death and inauguration.

Step by step solution

01

Part a. Step 1. Given information

Given,

INAUGURATION

DEATH


49

49

57

67


51

57

61

90


47

71

57

83


55

67

57

85


55

71

58

73


54

58

57

80


42

60

61

78


51

72

54

79


56

67

68

68


55

57

51

71


51

60

49

53


54

90

64

65


51

63

50

74


60

88

48

64


62

78

65

77


43

46

52

56


55

64

56

66


56

81

46

63


61

93

54

70


69

93

02

Part a. Step 2. Calculation

Find the standard error of the estimate by using MINITAB.

MINITAB procedure:

Step 1: Choose Stat > Regression > Regression.

Step 2: In Response, enter the column Death.

Step 3: In Predictors, enter the column Inauguration.

Step 4: Click OK.

MINITAB output:

From the MINITAB output, the standard error of the estimate is \(9.705\).

Interpretation:

The predicted scores in the sample differ on average from the observed scores by \(9.705\).

03

Part b. Step 1. Calculation

Construct the residual plot by using MINITAB.

MINITAB procedure:

Step 1: Choose Stat > Regression > Regression.

Step 2: In Response, enter the column Death.

Step 3: In Predictors, enter the column Inauguration.

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

Step 5: Click OK.

MINITAB output:

Construct the normal probability plot of residuals by using MINITAB.

MINITAB procedure:

Step 1: Choose Stat > Regression > Regression.

Step 2: In Response, enter the column Death.

Step 3: In Predictors, enter the column Inauguration.

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

Step 5: Click OK.

MINITAB output:

Thus, the residual plot and normal probability plot are obtained.

04

Part c. Step 1. Calculation

The assumption for regression inferences is given below:

The conditional mean of the response variable \((Y)\) is \(\beta _{0}+\beta _{1}X\), for each value \(X\) of predictor variable.

Equal standard deviation:

The standard deviation for the response variable \((Y)\) is same for the standard deviation for the explanatory variable \((X)\). The standard deviation is denoted as \(\sigma\).

Normal populations:

The distribution of the response variable follows normal.

Independent observations:

The observations of the response variable are independent of each other.

Check whether the graph suggests violation of one or more of the assumptions for the regression inferences.

  • From the residual plot, it is clear that the residuals are fall in the horizontal band.
  • From the normal probability plot of residuals, it is clear that the residuals are in the linear pattern.

Hence, the assumptions for the regression inferences are not violated for the variables death and inauguration.

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Most popular questions from this chapter

In Exercises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether you can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b)-(h).
b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
c. Find and interpret a 95% Te confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.
e. Find and interpret a95% prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.
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x243y357 role="math" localid="1652276835214" y^=2+x

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