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I need help figuring out what tests to use for SPSS. I think I did everything ri

ID: 3054658 • Letter: I

Question

I need help figuring out what tests to use for SPSS. I think I did everything right, but I'm having a hard time determining if i should use a T Test, a 1 Way Anova, etc.

Control

131

115

124

131

122

117

88

114

150

169

SCI

60

150

130

180

163

130

121

119

130

148

The purpose of a study by Tam et al was to investigate wheelchair maneuvering in individuals with lower spinal cord injury (SCI) and healthy controls (Control). Subjects used a modified wheelchair to incorporate a rigid seat surface to facilitate the specified experimental measurements. Interface pressure measurement was recorded by using a high-resolution pressure-sensitive mat with a spatial resolution of four sensors per square centimeter taped on the rigid seat support. During static sitting conditions, average pressures were recorded under the ischial tuberosities (bottom part of the pelvic bones). The data for measurements of the left ischial tuberosity (in mm Hg) for the SCI and control groups are shown in the Table. We wish to know if we may conclude, on the basis of these data, that, in general, healthy subjects exhibit lower pressure than SCI subjects.

Scientific/Research Hypothesis:

            Purpose: The purpose of the study conducted by Tam et al was to investigate wheelchair maneuvering in individuals with lower spinal cord injury (SCI) and healthy controls (control).

Research Hypothesis: The researchers hypothesize that healthy subjects will exhibit a lower mean pressure under the ischial tuberosities than subjects with a lower spinal cord injury.

Statistical/Test Hypothesis:

Null Hypothesis

H0: Mean Pressure of Healthy Controls = Mean Pressure of Spinal Cord Injury Subjects
Alternative Hypotheses

H1: Mean Pressure of Healthy Controls Mean Pressure of Spinal Cord Injury Subjects

H2:Mean Pressure of Healthy Controls > Mean Pressure of Spinal Cord Injury Subjects

Test Data & Assumptions:

The data consists of two groups of subjects (10 with a spinal cord injury and 10 without) that were observed using a modified wheelchair to determine the average pressure of the left ischial tuberosity in mm Hg. Since the dependent variable depends on the independent variable, the average pressure of left ischial tuberosity was deemed the dependent variable because it was dependent on the health of the subject (the independent variable).

            Non – Parametric or Parametric: Parametric (20 Subjects – 10 with a spinal cord injury, 10 without)

            Variables: 2

            Dependent Variables: Mean Pressure of the Left Ischial tuberosity (mm Hg)
            Independent Variables: Health of the Subject (Health of subject is in reference to whether or not they have a spinal cord injury)

Two Different Levels: With Spinal Cord Injury, No Spinal Cord Injury

            Data Collection: Samples were independently (randomly) obtained

           

Test Statistic & Decision Rule:

Tests Used: An independent samples and T - Test were used because I was trying to find evidence of a significant difference between two population means. The greater the T Value number is, the more likely it is that there is no significant difference. However, the closer the T Value is to 0, the more likely there isn’t a significant difference.

            Calculations:

Statistical Decision:

Null Hypothesis

H0: Mean Pressure of Healthy Controls = Mean Pressure of Spinal Cord Injury Subjects; reject null hypothesis


Alternative Hypotheses

H1: Mean Pressure of Healthy Controls Mean Pressure of Spinal Cord Injury Subjects; cannot reject

H2:Mean Pressure of Healthy Controls > Mean Pressure of Spinal Cord Injury Subjects; cannot reject

Statistical Conclusion:

            Question: Can we conclude, that on the basis of this data that, in general healthy subjects exhibit lower pressure than SCI subjects?

Yes, we can conclude, based on this data that general healthy subjects exhibit lower pressure than subjects with a spinal cord injury since the mean pressure underneath the left ischial tuberosity for healthy subjects was 126.1 +- 21.8 mmHG and the mean pressure underneath the left ischial tuberosity for individuals with a spinal cord injury was 133.1 +- 32.2 mmHG. Although, the difference in pressure reading, between the control group and the group of individuals with a spinal cord injury, is small.

Question 2

Young

Middle-aged

Elderly

193.6

125.4

59

137.5

126.5

87.2

122

115.9

84.4

145.4

98.8

78.1

117

94.3

51.9

105.4

99.9

57.1

99.9

83.3

54.7

74

72.8

78.6

74.4

83.5

53.7

112.8

96

In a study by Wang and colleagues, 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 and above). [Note: one value was missing in the middle-aged group]. One of the outcome measures was the force in Newtons required to fracture the bone. The following Table shows the data for the three groups. Analyze the data to determine if bone strength is different among the age groups.

Scientific/Research Hypothesis

            Purpose: The purpose of this experiment was to examine bone strength by measuring the force required to fracture a bone.

            Research Hypothesis: The researchers hypothesize that bone strength depends on the age group.

Statistical/Test Hypothesis

Null Hypothesis

H0: Mean Strength of Young Bones = Mean Strength of Middle Aged Bones = Mean Strength of Elderly Bones

Alternative Hypothesis

HA: Mean Strength of Young Bones Mean Strength of Middle Aged Bones Mean Strength of Elderly Bones

           

           

Test Data & Assumptions

            Non-Parametric or Parametric: Parametric (We can assume that the 3 populations or levels are normally distributed and have equal variances)

            Variables: 3

            Dependent Variables: Strength of Bones (Measured by the force required to Fracture Bones in Newtons)
            Independent Variables: Age Groups

Three Different Levels: Young (19-49 years), Middle-Aged (50-69 years) and Elderly (70 and above)

            Data Collection: Samples were independently (randomly) obtained

            Test Statistic & Decision Rule:

Tests Used: One – Way Anova

Calculation:

Statistical Decision:

Null Hypothesis

H0: Mean Strength of Young Bones = Mean Strength of Middle Aged Bones = Mean Strength of Elderly Bones; reject

Alternative Hypothesis

HA: Mean Strength of Young Bones Mean Strength of Middle Aged Bones Mean Strength of Elderly Bones; cannot reject    

Statistical Conclusion:

Question: Is bone strength different among the age groups?

Since we rejected the null hypothesis, we can conclude that bone strength is different among the age groups.

Question 3

Gold et al investigated the effectiveness on smoking cessation of a nicotine patch (NP), bupropion (BP), or both nicotine patch and bupropion (NP+BP). Consecutive consenting patients (n=164) assigned themselves to one of three treatments according to personal preference, resulting in the following sample size distributions: NP (n=13); BP (n=92), NP+BP (n=59). At their first smoking cessation class, patients estimated the number of packs of cigarettes they smoked per day and the number of years they smoked. The "pack years" is the average number of packs the subject smoked per day multiplied by the number of years the subject had smoked. The results of Pack Years are shown in the Table below for the 164 study participants. The researchers are curious about whether there might be differences in pack years among the treatment groups. Please analyze the data and provide an answer to satisfy the researchers' curiosity.

Pack Years

NP

BP

NP+BP

15

8

60

90

8

80

17

10

60

90

15

80

18

15

60

90

25

82

20

20

60

95

25

86

20

22

60

96

25

87

20

24

60

98

26

90

30

25

60

98

30

90

37

26

66

99

34

90

43

27

66

100

35

90

48

29

67

100

36

90

60

30

68

100

40

95

100

30

68

100

45

99

100

35

70

100

45

100

35

70

100

45

102

39

70

105

45

105

40

75

110

48

105

40

75

110

48

105

40

75

120

49

111

40

75

120

52

113

40

76

123

60

120

40

80

125

60

120

45

80

125

60

125

45

80

126

64

125

45

80

130

64

129

50

80

130

70

130

51

80

132

70

133

52

80

132

70

135

55

84

142

75

140

58

84

157

75

154

60

84

180

76

60

90

Scientific/Research Hypothesis:

            Purpose: The purpose of this experiment was to investigate the effectiveness on smoking cessation of a nicotine patch (NP), bupropion (BP), or both nicotine patch and bupropion (NP+BP).

            Hypothesis: The researchers hypothesize that there is a difference in pack years among treatment groups.

Statistical/Test Hypothesis:

Null Hypothesis

H0: Mean of Pack Years = Mean of Nicotine Patch = Mean of Bupropion = Mean of Nicotine Patch and Bupropion

Alternative Hypothesis

HA: Mean of Pack Years Mean of Nicotine Patch Mean of Bupropion Mean of Nicotine Patch and Bupropion

Test Data & Assumptions:

The result of the treatment option depends on the pack years.

            Non-Parametric or Parametric: Parametric

            Variables: 3

            Dependent Variables: Pack Years
            Independent Variables: Treatment Group

Three Levels: nicotine patch (NP), bupropion (BP), or both nicotine patch and bupropion (NP+BP)

            Data Collection:

            Test Statistic & Decision Rule:

Tests Used: Tukeys HSD, 1 Way Anova

                  a. Determine the appropriate test statistic to be used (considering the test data properties).

Parametric or nonparametric?

- Samples from normally distributed population?

- Samples independently (randomly) obtained (this applies to all tests)

- Similar variances among the populations? (Homoscedasticity)

- Variable measured on interval or ratio scale? (Values manipulable by conventional arithmetic?)

                  b. Decide whether this is a one-tailed or two-tailed test.

c. Define a critical value for the test statistic, ie, the cutoff point beyond which the null hypothesis would be rejected and the alternative hypothesis may be accepted (or cannot be rejected).

                  Consider the risks of Type I error (erroneously rejecting null hypothesis)

   or Type II error (erroneously rejecting the alternative hypothesis).

d. Anticipate whether the test has adequate power (sufficiently high probability that the null

hypothesis is correctly rejected).

Given that normality of uCA distribution can be assumed, there are two before-and-after groups to be compared, a paired samples t-test is selected for the data, and will be evaluated at an alpha value=0.05.

H1 pertains to alterations up or down, hence a two-tailed test will be applied.

H2 pertains to mean uCa (control) being smaller than uCa (vitD3), hence a one-tailed test will be applied.

Calculation:

Statistical Decision:

Statistical Conclusion:

Question: Is there a difference in pack years among the treatment groups?

Question 4

Anxiety patients admitted to a clinic were placed on a stress reduction study to assess the effectiveness of the program. Among the data collected were the patient scores on the Hamilton Anxiety Rating Scale at three different points in time: pretreatment, post-treatment, and three-month follow-up. Assuming that the Hamilton Scale is a continuous distribution with values between 0 and 56 within the studied population, was the stress reduction program effective in reducing the patients' stress scores?

HARS Scores

Subject

Initial

Pre

Post

3month

1

21

21

16

19

2

30

38

10

21

3

38

19

15

6

4

43

33

30

24

5

35

34

25

10

6

40

40

31

30

7

27

15

11

6

8

18

11

4

7

9

31

42

23

27

10

21

23

21

17

11

18

24

16

13

12

28

8

5

2

13

40

37

31

19

14

35

32

12

21

Scientific/Research Hypothesis

Purpose: The purpose of this experiment was to assess the effectiveness of a stress reduction program on patients who had anxiety.

Hypothesis: The researchers hypothesize that the stress reduction program was effective in reducing the patients’ stress scores.

Statistical/Test Hypothesis

H0 (Null Hypothesis): Mean of Pre Treatment = Mean of Post Treatment = Mean of Follow-up

HA (Alternative Hypothesis): Mean of Pre Treatment Mean of Post Treatment Mean of Follow-up

Test Data & Assumptions

            Non-Parametric or Parametric: Parametric

            Dependent Variables: HARS Score
            Independent Variables: Period of Time

Four Different Levels: Initial, Pre, Post, and 3 Month Follow Up

            Data Collection: Repeated Samples

            Test Statistic & Decision Rule:

Tests Used: One – Way Anova with Repeated Measures

Calculation:

Statistical Decision:

H0 (Null Hypothesis): Mean of Pre Treatment = Mean of Post Treatment = Mean of Follow-up; cannot reject

HA (Alternative Hypothesis): Mean of Pre Treatment Mean of Post Treatment Mean of Follow-up; cannot reject

Statistical Conclusion:

Question 5

In a study of pulmonary effects on guinea pigs, Lacroix et al exposed 18 ovalbumin-sensitized guinea pigs and 18 nonsensitized guinea pigs to regular air, benzaldehyde, and acetaldehyde. At the end of exposure the guinea pigs were anesthetized and allergic responses were assessed in bronchoalveolar lavage (BAL). The following table shows the alveolar cell count (x106) by treatment group for the ovalbumin-sensitized and nonsensitized guinea pigs. Test for differences (a) between ovalbumin-sensitized and nonsensitized outcomes, (b) among the three different exposures, and [c] interaction.

Ovalbumin-sensitized?

Treatment

Alveolar count (x106)

No

Acetaldehyde

49.9

No

Acetaldehyde

50.6

No

Acetaldehyde

50.35

No

Acetaldehyde

44.1

No

Acetaldehyde

36.3

No

Acetaldehyde

39.15

No

Air

24.15

No

Air

24.6

No

Air

22.55

No

Air

25.1

No

Air

22.65

No

Air

26.85

No

Benzaldehyde

31.1

No

Benzaldehyde

18.3

No

Benzaldehyde

19.35

No

Benzaldehyde

15.4

No

Benzaldehyde

27.1

No

Benzaldehyde

21.9

Yes

Acetaldehyde

90.3

Yes

Acetaldehyde

72.95

Yes

Acetaldehyde

138.6

Yes

Acetaldehyde

80.05

Yes

Acetaldehyde

69.25

Yes

Acetaldehyde

31.7

Yes

Air

40.2

Yes

Air

63.2

Yes

Air

59.1

Yes

Air

79.6

Yes

Air

102.45

Yes

Air

64.6

Yes

Benzaldehyde

22.15

Yes

Benzaldehyde

22.75

Yes

Benzaldehyde

22.15

Yes

Benzaldehyde

37.85

Yes

Benzaldehyde

19.35

Yes

Benzaldehyde

66.7

Scientific/Research Hypothesis

Purpose: The purpose of this experiment was to study the pulmonary affects different treatments have on guinea pigs.

Hypothesis: The researchers hypothesize that there is a difference that occurs between ovalbumin-sensitized and nonsensitized outcomes, among the three different exposures, and interaction.

Statistical/Test Hypothesis

Ovalbumin Sensitized & Non-Sensitized Guinea Pigs

H0 (Null Hypothesis): Mean of Ovalbumin Sensitized = Mean of Non- sensitized guinea pigs

HA (Alternative Hypothesis): At least two of the means differ

Three Different Exposures

H0 (Null Hypothesis): Mean of Benzaldehyde = Mean of Air = Mean of Acetaldehyde

HA (Alternative Hypothesis): At least two of the means differ

            Interaction

H0 (Null Hypothesis): Interaction does not exist.

HA (Alternative Hypothesis): Interaction does exist.

Test Data & Assumptions

There were two groups of guinea pigs, one that had

Non-Parametric or Parametric

Dependent Variables: Aveolar Count

Independent Variables: Treatment and Ovalbumin Sensitivity

Three Levels of Treatment: Regular Air, Benzaldehyde, and Acetaldehyde

Data Collection

            Test Statistic & Decision Rule:

Tests Used: Two – Way Anova / Univariate Analysis of Variance with Descriptive Power

Post Hoc Test: Tukey HSD, Duncan

Calculation:

Statistical Decision:

Ovalbumin Sensitized & Non-Sensitized Guinea Pigs

H0 (Null Hypothesis):Mean of Ovalbumin Sensitized = Mean of Non- sensitized guinea pigs; cannot reject

HA (Alternative Hypothesis): At least two of the means differ; cannot reject

Three Different Exposures

H0 (Null Hypothesis):Mean of Benzaldehyde = Mean of Air = Mean of Acetaldehyde; cannot reject

HA (Alternative Hypothesis): At least two of the means differ; cannot reject

            Interaction

H0 (Null Hypothesis):Interaction does not exist.

HA (Alternative Hypothesis): Interaction does exist. ; cannot reject

Statistical Conclusion:

Control

131

115

124

131

122

117

88

114

150

169

SCI

60

150

130

180

163

130

121

119

130

148

Explanation / Answer

1) I need help figuring out what tests to use for SPSS. I think I did everything right, but I'm having a hard time determining if i should use a T Test, a 1 Way Anova, etc.

Purpose: The purpose of the study conducted by Tam et al was to investigate wheelchair maneuvering in individuals with lower spinal cord injury (SCI) and healthy controls (control).

Research Hypothesis: The researchers hypothesize that healthy subjects will exhibit a lower mean pressure under the ischial tuberosities than subjects with a lower spinal cord injury.

Two sample t-test.

2) Scientific/Research Hypothesis

            Purpose: The purpose of this experiment was to examine bone strength by measuring the force required to fracture a bone.

            Research Hypothesis: The researchers hypothesize that bone strength depends on the age group.

Here we use one way anova because we test three means.

Q.3)

Scientific/Research Hypothesis

            Purpose: The purpose of this experiment was to examine bone strength by measuring the force required to fracture a bone.

            Research Hypothesis: The researchers hypothesize that bone strength depends on the age group.

Here also we used one way anova with post hoc.

Q4)

Scientific/Research Hypothesis

Purpose: The purpose of this experiment was to assess the effectiveness of a stress reduction program on patients who had anxiety.

Hypothesis: The researchers hypothesize that the stress reduction program was effective in reducing the patients’ stress scores.

Here pre and post observations taken therefore we use one way anova with repeated measure.

Q.5) Scientific/Research Hypothesis

Purpose: The purpose of this experiment was to study the pulmonary affects different treatments have on guinea pigs.

Hypothesis: The researchers hypothesize that there is a difference that occurs between ovalbumin-sensitized and nonsensitized outcomes, among the three different exposures, and interaction.

Here we use two way anova.

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