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Topic Progress

Descriptive Statistics

Measures of center, spread, shape, and data visualization.

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Foundations of Probability

Sample spaces, probability rules, conditional probability, and Bayes' theorem.

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Discrete Probability Distributions

Random variables, PMFs, expected value, binomial, Poisson, and geometric distributions.

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Continuous Probability Distributions

PDFs, CDFs, normal, exponential, and uniform distributions.

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Sampling and Data Distributions

Population vs. sample, law of large numbers, central limit theorem, and sampling distributions.

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Statistical Inference: Estimation

Point estimation, maximum likelihood estimation, and confidence intervals.

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Statistical Inference: Hypothesis Testing

Null and alternative hypotheses, p-values, Type I/II errors, and t-tests.

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Analysis of Variance

One-way ANOVA, the F-test, multiple comparisons, and two-way ANOVA.

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Linear Regression and Correlation

Pearson correlation, OLS regression, residuals, and inference for coefficients.

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Non-Parametric Statistics

Chi-square tests, Mann-Whitney U, and Wilcoxon signed-rank tests.

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