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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

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

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