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National University *
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Course
BST 322
Subject
Medicine
Date
Apr 3, 2024
Type
docx
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2
Uploaded by BarristerGrasshopperPerson34
A pilot study was conducted to evaluate the effectiveness of pain alleviation in patients with facial shingles. 24 patients were randomly assigned to one of 2 treatment groups; rest vs. acupuncture. After two weeks of treatment, the subjects were then asked to rate their pain on a scale from 1 to 10 with 10 being
the most pain they have ever experienced. Two sample T hypothesis test:
μ
1
: Mean of Rest
μ
2
: Mean of Acupuncture
μ
1
- μ
2
: Difference between two means
H
0
: μ
1
- μ
2
= 0
H
A
: μ
1
- μ
2
≠ 0
(with pooled variances)
Hypothesis test results:
Difference
Sample
Diff.
Std. Err.
DF
T-Stat
P-value
μ
1
- μ
2
0.9166
0.9844
22
0.9311
0.3619
Two sample T confidence interval:
μ
1
: Mean of Rest
μ
2
: Mean of Acupuncture
μ
1
- μ
2
: Difference between two means
(with pooled variances)
95% confidence interval results:
Difference
Sample Diff.
Std.
Err.
DF
Critical t
L. Limit
U. Limit
μ
1
- μ
2
0.9166
0.9844
22
2.0738
-1.1248
2.9582
1. State the null and alternative hypothesis.
Null: There’s no difference between rest and acupuncture for relieving pain with patients with facial shingles
Alternative: There’s a difference between rest and acupuncture for relieving pain with patients with facial shingles
2. What is the value of t for the analysis?
T: 0.9311
3. Is this value significant and at what level? Why?
The t-stat of 0.9311 is below the critical t 2.0738 and the p-value 0.3619 is above the alpha level .05, meaning I failed to reject the null hypothesis and there is a difference between acupuncture and rest in pain alleviation for patients with facial
shingles.
4. Why is a pooled variance test allowed here while a separate variance t test is not appropriate?
We use pooled variance in the two independent groups are equal. If the groups were dependent, like the same subjects being tested again, we would use the separate variance t test.
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