PHMastering the Art of Statistical Decision Making through Hypothesis Testing
- Identify the key components of hypothesis testing, including null and alternative hypotheses, significance levels, and types of errors.
- Explain the rationale behind different types of hypothesis tests (e.g., t-tests, z-tests) and when each is appropriate to use.
- Apply the hypothesis testing framework to real-world data, performing tests to evaluate claims about population parameters.
- Analyze the results of hypothesis tests by interpreting p-values, confidence intervals, and the significance of results.
- Evaluate the outcomes of hypothesis tests, assessing the risk of Type I and Type II errors and the implications of these risks in decision-making.
- Create and communicate clear reports of statistical findings, including all relevant assumptions, calculations, and interpretations of hypothesis test results.