Covers basic probability theory, ANOVA, experimental design, and correlations, emphasizing the importance of planning multiple tests and power analysis.
Explores t-tests, confidence intervals, ANOVA, and hypothesis testing in statistics, emphasizing the importance of avoiding false discoveries and understanding the logic behind statistical tests.
Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Emphasizes the critical importance of understanding statistics to avoid errors in research and decision-making, using motivating examples and practical exercises.
Covers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.
