Testing Claims with Data

Hypothesis testing lets us use data to test if a claim about a population is likely to be true. We start with a null hypothesis (no effect) and see if evidence supports an alternative hypothesis (some effect).

The Steps

1. State the hypotheses.
2. Collect data.
3. Calculate a test statistic (like a z-score or t-score).
4. Find the p-value (the probability of seeing results at least this extreme if the null hypothesis is true).
5. Decide: If the p-value is low (usually < 0.05), reject the null hypothesis.

Real-World Decisions

Hypothesis testing is essential in medicine, science, and business to see if new ideas actually work.