R

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Last Update	09/20/2026
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Section 4: Data Manipulation

7Lessons ·
- 20: Joining Data Frames
  
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Section 5: Visualization and Statistics

6Lessons ·
- 24: Descriptive Statistics in R
  
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- 25: Basic Hypothesis Testing
  
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Section 7: Practical Projects

4Lessons ·
- 35: Building an R Markdown Report
  
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- 37: Building an Automated Statistical Report
  
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Section 8: Interview Practice

2Lessons ·
- 39: Comparing R and Python for Data Analysis
  
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Section 11: More Data Wrangling

3Lessons ·
- 48: Date and Time Handling with lubridate
  
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Section 13: Statistical Modeling Deep Dive

5Lessons ·
- 54: Generalized Linear Models in R
  
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- 55: ANOVA and Post-Hoc Tests
  
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- 58: Mixed-Effects Models with lme4
  
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Section 15: R Visualization Deep Dive

4Lessons ·
- 65: Interactive Visualizations with plotly
  
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Section 18: R and Databases

3Lessons ·
- 78: dbplyr for Remote Data Sources
  
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Section 20: Bioinformatics and Specialized R

3Lessons ·
- 84: Bioconductor Overview
  
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- 85: Genomic Data Analysis Basics in R
  
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- 86: Financial Time Series Analysis in R
  
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Section 22: More Practice Exercises

4Lessons ·
- 91: Practice Exercise: Building an End-to-End Data Analysis Pipeline
  
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Section 29: Advanced Statistical Techniques

5Lessons ·
- 117: Bayesian Statistics with brms
  
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- 118: Bootstrap Methods in R
  
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- 121: Factor Analysis in R
  
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Section 33: R for Clinical and Health Data

3Lessons ·
- 133: Clinical Trial Data Analysis in R
  
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- 134: Survival Curves and Kaplan-Meier Estimates Revisited
  
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Section 35: R Data Cleaning Deep Dive

4Lessons ·
- 140: Handling Outliers Systematically
  
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Section 37: More Practical Projects Round 2

4Lessons ·
- 149: Building an A/B Testing Analysis Pipeline
  
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Section 42: R for Marketing Analytics

4Lessons ·
- 168: Campaign Response Analysis
  
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Section 43: R Data Import/Export Deep Dive

4Lessons ·
- 169: Reading Excel Files with readxl
  
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Section 56: More Interview Practice Round 2

4Lessons ·
- 225: Mock Data Analysis Interview Walkthrough in R
  
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- 226: Timed Mock Assessment on Core R and Tidyverse
  
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Section 58: R for Environmental Science

4Lessons ·
- 231: Climate Data Analysis in R
  
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- 234: Air Quality Data Analysis in R
  
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Section 59: R Notebook and Documentation Practices

4Lessons ·
- 238: Version-Controlling Data Analysis Notebooks
  
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Section 60: More Data Wrangling Mastery

4Lessons ·
- 239: Practice Exercise: Reshaping Wide-to-Long Data with Complex Keys
  
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- 240: Practice Exercise: Merging Multiple Messy Data Sources
  
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Section 61: R for A/B Testing at Scale

4Lessons ·
- 243: Multiple Testing Correction Methods
  
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- 245: Bayesian A/B Testing Approaches
  
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