Statistical Methods & Thinking

By Weijing Wang @ NYCU

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Episodes: 13

Description

The materials in this podcast are generated by NotebookLM based on the lecture notes of the course Applied Statistical Methods, offered at NYCU and taught by Weijing Wang. The podcast covers core methods for analyzing associations in data, including correlation analysis, simple and multiple linear regression (estimation, testing, and model checking), and discussions on association versus causation. It also introduces methods for categorical data analysis such as contingency tables, chi-square tests, logistic regression, and the generalized linear model framework.

Episode Date
Episode 13 | Survival Analysis: Making Sense of Time-to-Event Data
Feb 03, 2026
Episode 12 | Clustering and Classification: Finding Structure in Data
Feb 03, 2026
Episode 11 | Finding Structure in Multivariate Data
Feb 02, 2026
Episode 10 | From Chi-Square to GLMs: Beyond Linear Regression
Feb 02, 2026
Episode 9 | Categorical Data in Practice: Measures of Association, and Simpson’s Paradox
Feb 02, 2026
Episode 8 | Two-Way ANOVA and Beyond
Feb 01, 2026
Episode 7 | Design of Experiments
Feb 01, 2026
Episode 6 | Model Selection Strategies
Feb 01, 2026
Episode 5 | Deeper in Multiple Linear Regression
Jan 31, 2026
Episode 4|Multiple Linear Regression
Jan 31, 2026
Episode 3|Association, Inference, and Causal Thinking in Simple Linear Regression
Jan 31, 2026
Episode 2|Simple Linear Regression
Jan 31, 2026
Episode 1|Seeing Association in Data: Scatter Plots and Correlation
Jan 31, 2026