PSYCH 100A Lecture Notes - Lecture 7: Type I And Type Ii Errors, Null Hypothesis, Statistical Hypothesis Testing
Document Summary
A statistical method that uses sample data to evaluate a hypothesis about a population. The general goal of a hypothesis test is to rule out chance (sampling error) as a plausible explanation for the results from a research study. Null hypothesis: no change; no difference; the treatment has no effect: h0: with supplement = 80. Critical region: extreme sample values defined by level, used to reject/retain h0. Q: (t/f) if the alpha level increased from = . 01 to = . 05, the size of the critical region also increases. True: collect data and compute sample statistics. Summarize the data with appropriate descriptive statistics (i. e. mean: sample mean after 6 months of treatment = 92. Compare sample mean with population mean via z-score: z , z , make a decision based on . 05 z = Type i error (*most important to consider) is the probability of rejecting the h0 when it is actually true.
