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Answer :
Therefore, we can say with 95% confidence interval that the true difference in mean body temperatures between men and women is between -1.144 and -0.056 degrees Fahrenheit.
a) Hypothesis test setup:
Let μ1 be the population mean body temperature of men and μ2 be the population mean body temperature of women.
Null hypothesis: H0: μ1 = μ2 (The mean body temperature is the same for men and women)
Alternative hypothesis: Ha: μ1 ≠ μ2 (The mean body temperature differs for men and women)
We will use a two-sample t-test for independent samples to test this hypothesis.
b) The exact p-value for the two-sample t-test with the given data is 0.0117. This p-value indicates that if the null hypothesis were true, the probability of obtaining a sample as extreme as the observed sample (or more extreme) is 0.0117. Since this p-value is less than the commonly used significance level of 0.05, we reject the null hypothesis and conclude that there is sufficient evidence to indicate that mean body temperatures differ for men and women.
c) To construct a 95% confidence interval for the difference in population means (μ1 - μ2), we can use the following formula:
CI = (x1 - x2) ± tα/2,ν * SE
where x1 and x2 are the sample means for men and women, tα/2,ν is the t-value for the desired confidence level and degrees of freedom (df), and SE is the standard error of the difference in sample means.
Using the given data, we have:
x1 = 97.5, x2 = 98.4
s1 = 0.35, s2 = 0.366
n1 = 8, n2 = 9
df = n1 + n2 - 2 = 15
t0.025,15 = 2.131 (from t-distribution table)
SE = sqrt(s1^2/n1 + s2^2/n2) = 0.126
CI = (97.5 - 98.4) ± 2.131 * 0.126
CI = (-1.144, -0.056)
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