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Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.
Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.
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.
Covers the basics of t tests, including hypothesis testing, significance levels, P-values, Z-tests, and the t distribution.
Covers t-tests, p-values calculation, and comparison of coefficients.
