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Introduction to Data Science (DS 215)
·
Module 8
Hypothesis Testing and Statistical Significance
1
Formulating Hypotheses
Formulate null and alternative hypotheses for a given research question.
2
Likelihood Ratio Tests for Simple Hypotheses
Derive the Likelihood Ratio Test (LRT) statistic for simple hypotheses.
3
Type-I, Type-II Errors, and Statistical Power
Explain the mathematical trade-off between Type-I and Type-II errors and the concept of statistical power.
4
Deriving the One-Sample T-Test Statistic
Derive the one-sample t-test statistic from its definition.
A/B Test Analysis with SciPy
Project: Perform an A/B test analysis on a sample dataset, from hypothesis formulation to p-value interpretation, using SciPy.
Previous module
Principles of Bayesian Inference
Next module
Linear Regression and the Bias-Variance Tradeoff