What you’ll learn to do: Given a claim about a population, construct an appropriate set of hypotheses to test and properly interpret p values and Type I / II errors. 
Hypothesis testing is part of inference. Given a claim about a population, we will learn to determine the null and alternative hypotheses. We will recognize the logic behind a hypothesis test and how it relates to the P-value as well as recognizing type I and type II errors. These are powerful tools in exploring and understanding data in real-life.
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- Concepts in Statistics. Provided by: Open Learning Initiative. Located at: http://oli.cmu.edu. License: CC BY: Attribution
- Inferential Statistics Decision Making Table. Provided by: Wikimedia Commons: Adapted by Lumen Learning. Located at: https://upload.wikimedia.org/wikipedia/commons/thumb/e/e2/Inferential_Statistics_Decision_Making_Table.png/120px-Inferential_Statistics_Decision_Making_Table.png. License: CC BY: Attribution