Here are the essential concepts you must grasp in order to answer the question correctly.
Null Hypothesis (H0)
The null hypothesis is a statement that there is no effect or no difference, and it serves as a starting point for statistical testing. In this context, the null hypothesis would assert that the mean difference between the body temperatures at 8 AM and 12 AM is equal to 0°F, indicating no significant change in temperature over the time period.
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Alternative Hypothesis (H1)
The alternative hypothesis is a statement that contradicts the null hypothesis, suggesting that there is an effect or a difference. For this scenario, the alternative hypothesis would propose that the mean difference between the body temperatures at 8 AM and 12 AM is not equal to 0°F, indicating a significant change in temperature.
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Mean Difference
The mean difference refers to the average of the differences between paired observations—in this case, the body temperatures measured at 8 AM and 12 AM. Calculating this mean difference is essential for hypothesis testing, as it helps determine whether the observed changes in temperature are statistically significant or could have occurred by random chance.
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Difference in Means: Confidence Intervals