What is a hypothesis test?

Hypothesis testing is a way to test a claim about a given population. It enables you to determine whether or not an outcome of a given sample was due to random chance or was statistically significant.

Scenario: The Delta Apple Pi chapter at Crammer Nation University claims that their brothers get on average 25 Tinder matches per day. You have a hunch that their daily Tinder matches are actually lower than that, so you collect a random sample of 35 Delta Apple Pi brothers' daily Tinder matches. You measure a mean of 23.5 daily matches with a standard deviation of 5.7 matches. Provide support for your claim using a hypothesis test with an alpha level of 0.05.

This hypothesis test will yield one of two outcomes:

• We do have enough evidence to reject Delta Apple Pi's claim of 25 average Tinder matches per day.
• We don't have enough evidence to reject (a.k.a. "fail to reject") Delta Apple Pi's claim of 25 average Tinder matches per day.

Your hypothesis test will make a claim about the population parameter (µ or p), not the sample parameter (x-bar or p-hat)!

You'll need to...

1. State the null hypothesis.
2. State the alternative hypothesis.

You'll calculate a standard score (z-score, t-score, X² score, etc.) based on the sample and population data.

Given the...

• Test statistic
• Alternative hypothesis (one-tail vs. two-tail)

...you'll need to discern the p-value (a.k.a. the probability of your sample occurring).