Statistical Hypothesis Testing: Basics and Applications

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Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

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

Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Provides an overview of hypothesis testing, p-values, Wald test, and non-parametric statistics.

Introduces hypothesis testing, focusing on the Z-test and critical regions.

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.

Explores hypothesis testing in statistics, focusing on decision-making based on sample data and controlling error probabilities.