What information does a hypothesis test provide versus a confidence interval?

What information does a hypothesis test provide versus a confidence interval? How is this utilized in health care research? Provide a workplace example that illustrates your ideas. If you are not currently working in health care, to answer this question, research a local hospital or health care organization and provide an example of how they utilize inferential statistics.
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ANSWER
Hypothesis Tests vs. Confidence Intervals in Healthcare Research
Hypothesis tests and confidence intervals are two fundamental statistical concepts used in healthcare research to analyze data and draw conclusions about populations. While both techniques provide valuable insights, they serve distinct purposes and address different questions.
Hypothesis Tests
A hypothesis test evaluates whether there is enough evidence to reject a null hypothesis, which typically states there is no difference between groups or no association between variables. It determines whether the observed data is significantly different from what would be expected under the null hypothesis.
A hypothesis test involves three key components:
Null Hypothesis: A statement about the population parameter that is assumed to be true unless there is enough evidence to reject it.
Alternative Hypothesis: A statement about the population parameter that contradicts the null hypothesis.
Statistical Significance: A level of confidence, typically set at 0.05, at which the null hypothesis is rejected if the probability of the observed data or more extreme data is less than or equal to this significance level.
Confidence Intervals
In contrast, a confidence interval provides a range of values that likely contains the true population parameter. It estimates the precision of the sample statistic and the uncertainty associated with the estimate.
A confidence interval is calculated based on the sample size, the sample mean, and the standard error of the mean. It is typically expressed as the mean ± margin of error.
Utilization in Healthcare Research
Both hypothesis tests and confidence intervals are widely used in healthcare research to answer various questions:
Hypothesis tests: Does a new drug treatment significantly improve patient outcomes compared to the standard treatment?
Confidence intervals: What is the average blood pressure for a population of healthy adults?
Workplace Example
Consider a clinical trial evaluating a new drug for treating chronic pain. The researchers hypothesize that the new drug will reduce pain scores more effectively than the placebo. They conduct a hypothesis test and determine that the observed difference between the two treatment groups is statistically significant. This provides strong evidence to support the hypothesis and suggest that the new drug is more effective in reducing pain.
In addition, the researchers calculate a confidence interval for the difference in pain scores between the two groups. The confidence interval indicates that the true mean difference in pain scores is likely to fall between a certain range. This information can be used to inform prescribing guidelines and communicate the uncertainty associated with the estimate.
References
Agresti, A., & Franklin, C. (2016). Statistical methods for the social sciences (6th ed.). Pearson Education.
Gravetter, F. J., & Wallnau, L. B. (2019). Essentials of statistics for the behavioral sciences (11th ed.). Cengage Learning.