This class covers the fundamentals of hypothesis testing, e.g. Type I and Type II errors, statistical power, p-values, and confidence intervals, and the connection between these terms. Multiplicity adjustment for multiple comparisons, as well as common mistakes and misconceptions are discussed. The Bayesian approach is briefly described.
Information is presented in non-technical terms, and emphasis is on understanding the concepts rather than theory and formulas.
At the end of the class, participants should have a good enough grasp of the fundamentals of hypothesis testing to understand basic statistical results, and to communicate with biostatisticians more efficiently.
Plenty of time is devoted to questions to and from participants. References are provided for more in-depth self-study.
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