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Course Collection
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Statistics II: Inference
A comprehensive deep dive into statistical inference. This collection covers Bayesian methods, hypothesis testing frameworks, and practical Python implementations for data analysis.
Course Modules
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01
Introduction to Probability
Foundational concepts: Sample space, events, axioms of probability.
10 MIN READ
COMPLETED
02
Bayesian Inference
Priors, Likelihoods, and Posterior distributions with Python.
15 MIN READ
COMPLETED
Hypothesis Testing
Null vs Alternative, P-values, and Type I/II errors.
20 MIN READ
IN PROGRESS
04
Linear Regression
Least squares, R-squared, and residual analysis.
18 MIN READ
LOCKED
05
Logistic Regression
Classification problems, sigmoid functions, and decision boundaries.
22 MIN READ
LOCKED