DQ 2 : Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis

Get the logic right before the examples, because the rejection criterion is what most posts state loosely. The null hypothesis is a statement of no effect or no difference. A test asks: if the null were true, how probable would data at least this extreme be? That probability is the p-value, and if it falls below a threshold set in advance — conventionally 0.05 — the null is rejected. Two things follow that are worth writing. The threshold is a convention chosen for a tolerable false-positive rate, not a fact about nature, and it is set before the analysis rather than after. And rejection is not proof: p below 0.05 means the data are unlikely under the null, which is not the same as the alternative being true, and failing to reject is not evidence of no effect, particularly in a small study. Getting the logic exact matters here, because you will have to say it to a patient.

Choose two examples that use hypothesis testing differently rather than two of the same shape. A clinical trial comparing readmission rates between usual discharge and a pharmacist-led medication reconciliation is a difference-between-groups test. A study asking whether nurse staffing ratio is associated with fall rate is a relationship test. Then the practice half. This matters at the bedside because it is what stops you overstating a finding to a patient: a significant result in a trial of a drug tells you the effect is unlikely to be chance, not that it will work for this person, and the confidence interval tells you how large the effect plausibly is. It also protects you the other way, since a study that failed to reach significance has not shown that a treatment does not work. Say how you would phrase that to a patient, and the last clause is answered properly rather than gestured at.