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To help you navigate, here is a list of my articles based on content: 👇
- Analyzing Survey Data in R: A Crash Course (Part 1)
- Analyzing Survey Data in R: A Crash Course (Part 2)
Analyzing Data: Self Reflection
- Analyzing Data in Social Science vs. Engineering: Key Differences to Keep In Mind
- Five Reasons Why Statistics is So Hard to Learn
- How to Explore the Effect of Doing Something: Applied Causal Inference 101 (Part 1)
- How to Explore the Effect of Doing Something: Applied Causal Inference 101 (Part 2)
- Why Is Correlation Neither Necessary Nor Sufficient for Causation?
- Regression and Causal Inference: How Causal Graphs Helped Me Overcome 3 Key Misconceptions
- Confounding Variable and Spurious Correlation: Key Challenge in Making Causal Inference
- Endogenous Selection/Collider Bias: Another Key Issue in Causal Inference
Descriptive Statistics (Table & Data Visualization)
- Create LaTeX Tables in R
- Create Heatmap in R Using ggplot2
- Create Line Charts in R Using ggplot2
- Visualize Continuous Data with ggplot2 in R
- Visualize Gapminder Data in R
- Statistical Significance: Are You Interpreting Correctly?
- Confidence Interval: Are You Interpreting Correctly?
- Why You Should Prefer Confidence Interval over p-value
- Understanding Regression Output: A Lesson for Absolute Beginners (Part 1)
- Understanding Regression Output: A Lesson for Absolute Beginners (Part 2)
- Regression and Causal Inference: Which Variables Should Be Added to The Model?
- What Does It Mean to Control for A Variable in Regression?
- Interpreting Regression Coefficient: Wish I Had Known This Before
- Interpreting the Coefficients of a Regression with an Interaction Term: A Detailed Explanation