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CC6104 Statistical Thinking

The purpose of this course is to introduce students to statistical thinking, a systematic way of thinking to describe "real world" phenomena taking into account their inherent uncertainty and using data for decision making.

The course introduces the fundamentals of statistical thinking, which are descriptive data analysis, statistical programming in R, and probability theory. It then teaches the two most important schools of statistical inference: frequentist inference and Bayesian inference. Finally, advanced topics such as model evaluation using information theory, directed graphical models for modeling conditional dependencies between variables, and multilevel models are discussed.

Slides

PART I: Foundations

  1. Introduction to Statistical Thinking | (tex source file), video 1, video 2
  2. Introduction to R | (tex source file), video 1, video 2, video 3, video 4
  3. Descriptive Statistics | (tex source file), video 1, video 2, video 3, video 4
  4. Probability | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6

PART II: Frequentist Inference

  1. Introduction to Statistical Inference | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6, video 7, video 8
  2. Design of Experiments & Hypothesis Testing | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6
  3. Linear Regression | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6

Part III: Bayesian Inference

  1. Introduction to Bayesian Inference | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6, video 7
  2. Summarizing the Posterior | (tex source file), video 1, video 2, video 3, video 4
  3. Bayesian Linear Regression | (tex source file), video 1, video 2, video 3, video 4, video 5
  4. Markov Chain Monte Carlo | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6

Part IV: Other Topics

  1. Model Evaluation and Information Criteria | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6
  2. Directed Graphical Models | (tex source file), video 1, video 2, video 3, video 4, video 5, video 6
  3. Generalized and Multilevel Linear Models | (tex source file) (Work in Progress: Chapter 13 of Statistical Rethinking)

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Teaching material of the course "Statistical Thinking" of the Department of Computer Science at the University of Chile.

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