Workplace Example:

Consider a local hospital assessing the impact of a new infection control protocol on the rate of hospital-acquired infections (HAIs).

Hypothesis Test:

• Research Question: Does the new protocol reduce the rate of HAIs compared to the old protocol?
• Null Hypothesis : The new protocol does not reduce the rate of HAIs.
• Alternative Hypothesis : The new protocol reduces the rate of HAIs.
• The hospital collects data on HAIs before and after implementing the protocol and conducts a hypothesis test to determine if the observed reduction is statistically significant.

Confidence Interval:

• In addition to the hypothesis test, the hospital calculates a confidence interval for the reduction in HAIs. For example, a 95% CI might indicate that the reduction in HAIs is between 5% and 15%.
• This interval helps the hospital understand the range of possible impacts the protocol might have, providing a clearer picture of its effectiveness.

Conclusion: Combining hypothesis testing and confidence intervals offers a robust approach to making informed decisions, ensuring that interventions are both