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1. In a study by Wang et al., researchers examined bone strength. They collected

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Question

1. In a study by Wang et al., researchers examined bone strength. They collected 10 cadaveric femurs from subjects in three age groups: young (19-49 years), middle-aged (50-69 years), and elderly (70 years or older) [Note: one value was missing in the middle-aged group]. One of the outcome measures (W) was the force in Newtons required to fracture the bone. The results are presented below:

Young (Y)

Middle-aged (MA)

Elderly (E)

193.6

125.4

59.0

137.5

126.5

87.2

122.0

115.9

84.4

145.4

98.8

78.1

117.0

94.3

51.9

105.4

99.9

57.1

99.9

83.3

54.7

74.0

72.8

78.6

74.4

83.5

53.7

112.8

96.0

Test the hypothesis to see if you can conclude that there is a difference among population means. Let = .05. Use Tukey’s HSD procedure to test for significant differences among individual pairs of means. (20 marks) Note: Use SPSS Data1 to answer the question

1.Inn a study by Wang et al., researchers examined bone strength. They collected 10 cadaveric femurs from subjects in three age groups: young (19-49 years), middle-aged (50-69 years), and elderly (70 years or older) [Note: one value was missing in the middle-aged group]. One of the outcome measures (W) was the force in Newtons required to fracture the bone. The results are presented below

Wheelchair Use

Yes

No

Fallers

62

121

Nonfallers

18

32

Do these data provide sufficient evidence to warrant the conclusion that wheelchair use and falling are related? Let = .05                                                   (15 marks)

Note: Use SPSS Data 2 to answer the question

2.Kindergarten students were the participants in a study conducted by Susan Bazyk et al. The researchers studied the fine motor skills of 37 children receiving occupational therapy. They used an index of fine motor skills that measured hand use, eye-hand coordination, and manual dexterity before and after 7 months of occupational therapy. Higher values indicate stronger fine motor skill. The scores appear in the following table.

Subject

Pre

Post

Subject

Pre

Post

1

91

94

20

76

112

2

61

94

21

79

91

3

85

103

22

97

100

4

88

112

23

109

112

5

94

91

24

70

70

6

112

112

25

58

76

7

109

112

26

97

97

8

79

97

27

112

112

9

109

100

28

97

112

10

115

106

29

112

106

11

46

46

30

85

112

12

45

41

31

112

112

13

106

112

32

103

106

14

112

112

33

100

100

15

91

94

34

88

88

16

115

112

35

109

112

17

59

94

36

85

112

18

85

109

37

88

97

19

112

112

Can one conclude on the basis of these data that after 7 months, the fine motor skills in a population similar subjects would be stronger? Let a = .05. Determine the p value. (15 marks)

Note: Use SPSS to answer the question

3.The following are the pulmonary blood flow (PBF) and pulmonary blood volume (PBV) values recorded for 16 infants and children with congenital heart disease:

y

PBV (ml/sqM)

167
280
394
420
303
429
602
522
224
291

233

370

531

516

211

439

X

PBF (L/min/sqM)

4.32
3.40

6.25

17.30

12.30
13.99

8.74
8.90
5.87
5.00

3.51

4.24

19.41

16.61

7.21

11.60

Find the regression equation describing the linear relationship between the two variables. Let = .05.

                                                                                                                                 (15 marks)

Note: Use SPSS to answer the question

In a study of the relationship between creatinine excretion, height, and weight, the data shown in the following table were collected on 20 infant males:

Creatinine

Excretion

(mg/day)

Weight (kg)

Height (em)

Infant

y

X1

X2

1

105

9

72

2

115

    11

76

3

53

6

59

4

85

8

67

5

135

10

60

6

58

5

58

7

90

8

70

8

60

7

65

9

45

4

54

10

125

11

83

11

86

7

64

12

80

7

66

13

65

6

61

14

95

8

66

15

25

5

57

16

125

11

81

17

40

6

59

18

95

9

     71

19

70

6

         62

20

   120

10

     75

(a) Find the multiple regression equation describing the relationship among these variables.                                                                                               (15 marks)
(b) Let X1 = 9 and X 2 = 58 and find the predicted value of Y.             (5 marks)

                       

Note: Use SPSS to answer the question

6.LaMont et al. tested for obstructive coronary artery disease (OCAD) among 113 men
and 35 women who complained of chest pain or possible equivalent to their primary care
physician. Following Table shows the cross-classification of OCAD with gender. We wish to
use logistic regression analysis to determine how much greater the odds are of finding
OCAD among men than among women.                                           (15 marks)

Table: Cases of Obstructive Coronary Artery Disease (OCAD) classified by sex

Disease

Males

Females

Total

OCAD present

92

15

107

OCAD not present

21

20

41

Total

113

35

148

Note: Use SPSS to answer the question

Young (Y)

Middle-aged (MA)

Elderly (E)

193.6

125.4

59.0

137.5

126.5

87.2

122.0

115.9

84.4

145.4

98.8

78.1

117.0

94.3

51.9

105.4

99.9

57.1

99.9

83.3

54.7

74.0

72.8

78.6

74.4

83.5

53.7

112.8

96.0

Explanation / Answer

Result: first problem solved.

(a) Find the multiple regression equation describing the relationship among these variables.                                                                                               (15 marks)

SPSS OUTPUT

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.937a

.878

.863

11.584

a. Predictors: (Constant), x2, x1

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

16383.688

2

8191.844

61.050

.000b

Residual

2281.112

17

134.183

Total

18664.800

19

a. Dependent Variable: y

b. Predictors: (Constant), x2, x1

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

12.287

30.451

.403

.692

x1

16.250

2.652

1.117

6.126

.000

x2

-.812

.707

-.209

-1.147

.267

a. Dependent Variable: y

The regression equation is

Y=12.287+16.250*x1-0.812*x2

(b) Let X1 = 9 and X 2 = 58 and find the predicted value of Y.             (5 marks)

Predicted y = 12.287+16.250*9-0.812*58

=111.441 (mg/day)

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.937a

.878

.863

11.584

a. Predictors: (Constant), x2, x1