Lectures related to Exploratory Statistics: Data Analysis Fundamentals

Explores funding an idea, big data analysis, and statistics basics with insights on avoiding common pitfalls.

Understanding Statistics & Experimental Design

Covers statistics, experimental design, errors, distributions, implications of sample size, and null results.

Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.

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

Understanding Statistics & Experimental Design

Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.

Statistical Hypothesis Testing: Inference and Interpretation

Explores statistical hypothesis testing, including constructing confidence intervals, interpreting p-values, and making decisions based on significance levels.