Statistics Essentials: Chi-Square Test

Related lectures (31)

Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.

Covers hypothesis testing, types of errors, Neyman-Pearson framework, and one-sided Gaussian tests.

Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.

Explores unilateral and bilateral pairs in statistical hypothesis testing, covering critical values, test statistics, and p-values.

Explores the impact of a binary covariate on binary responses using 2x2 tables.

Covers the estimation of theoretical frequencies and independence testing between two characteristics, with examples for practical application.

Explains the Chi-Square test for independence hypothesis and its practical applications.

Introduces the chi-squared test for hypothesis testing against theoretical distributions, showcasing its application with dice fairness testing.

Explains hypothesis testing using T-test and Chi-square test to compare means and assess independence of variables.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Explores the theory and applications of likelihood ratio tests in statistical hypothesis testing.

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