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National University *

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BST 322

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Medicine

Date

Apr 3, 2024

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2

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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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