Outline of notes

• Getting Started
  1. R, RStudio, R Markdown
  2. Coding Best Practices
• Introduction
• Handling Data
  1. Basics of Data Wrangling
  2. Wrangling in the tidyverse
  3. A data cleaning pipeline for research projects
• [In Progress] Descriptive Statistics
• [In Progress] Data Visualization
• The Linear Model
  1. Linear Regression
  2. Logistic Regression
  3. [In Progress] Interactions
  4. [In Progress] Model Selection
  5. [In Progress] Mixed-effects linear models
• [In Progress] A discussion on probabilities and probability distributions
• [In Progress] Simulations (I)
  1. Monte Carlo Simulations
  2. The Bootstrap
• [In Progress] Simulations (II): Statistics in Machine Learning
  1. Understanding the statistics of machine learning models
• [In Progress] Data Mining
• Introduction to Time Series Data
  1. Time Series Basics
  2. Smoothing-based models
  3. Time-Series Regression
• Optimization
  1. Linear Optimization
  2. Integer-valued Optimization

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