PY 355 Lecture Notes - Lecture 13: Type I And Type Ii Errors, Null Hypothesis, Statistical Inference

• School: University of Alabama
• Department: Psychology
• Course: PY 355
• Professor: Craig Walter Cummings

Document Summary

We cannot say that we accept the null hypothesis because the null hypothesis can never be proven. Errors: type i error: a researcher rejects the null hypothesis when it is true. Beta: the probability of making a type ii error (and erroneously failing to find an effect that was actually present) Statistical decisions and outcomes null hypothesis is false reject null hypothesis fail to reject null hypothesis correct decision type ii error null hypothesis is true type i error correct decision. Effect size: effect size: an index of the strength of the effect of the independent variable on the dependent variable. Finding the critical value: calculate the degrees of freedom. Hypotheses: directional hypothesis: states which of the two condition means is expected to be larger. Use a one-tailed test: nondirectional hypothesis: states that the two means are expected to differ but does not specify which will be larger.