Statistics – Common Mistakes,"This note focuses on common mistakes within the broader subject of Statistics. It starts with a high-level overview that explains why this topic is important and where it fits in your overall learning journey. The content is divided into short, digestible sections so you can move through the material in focused study bursts using Noteflix. Each section includes clear explanations, simple language, and illustrative examples that make the ideas behind common mistakes easier to understand. You will also find quick self-check prompts designed to help you actively recall information instead of just re-reading it passively. Key terms and formulas are highlighted so you can rapidly scan the note when you come back for spaced repetition or last-minute review. By the end of this note, you should feel more confident applying these ideas in homework, projects, and exams related to statistics."
This note highlights common mistakes in statistics, emphasizing the importance of avoiding them for accurate data analysis and interpretation. It covers topics such as correlation vs. causation, sampling bias, the base rate fallacy, p-hacking, statistical power, survivorship bias, regression to the mean, and overfitting/underfitting, providing examples and methods to mitigate these errors.
Key points
- Distinguish between correlation and causation.
- Be aware of sampling bias and its impact on generalizability.
- Consider the base rate when assessing probabilities.
- Avoid p-hacking and adjust for multiple comparisons.
- Ensure adequate statistical power to detect true effects.
- Recognize and account for survivorship bias and regression to the mean.
- Balance model complexity to avoid overfitting and underfitting.