Master inferential statistics: estimation, point and interval estimation, hypothesis testing, null and alternative hypotheses, significance levels, Type I and Type II errors, and statistical power.
Master the concept of levels of significance (0.05 and 0.01), confidence limits, the meaning of α, and how these form the decision framework for hypothesis testing in psychological research.
In-depth guide to null and alternative hypotheses, directional vs. non-directional predictions, Type I and Type II errors in hypothesis testing, and the scientific importance of hypothesis formulation in psychological research.
Master the theory and formulas for testing whether two sample means differ significantly — covering null hypothesis, critical ratio, levels of significance, and one- vs two-tailed tests.
Understand the core logic of hypothesis testing in psychology: the five-step process, null and research hypotheses, comparison distributions, cutoff scores, and Z-scores.