Understanding Statistical Errors and Reproducibility

📋 Course Outline

1. Statistical Errors and Hypothesis Testing
2. Type I and Type II Errors
3. P Values and False Positives
4. Reproducibility Crisis in Psychology
5. Publication Bias and Transparency
6. Multiple Comparisons and HARKing
7. Researcher Degrees of Freedom
8. False Positive Psychology and Study Design
9. Reporting Guidelines for Authors and Reviewers

📖 1. Statistical Errors and Hypothesis Testing

🔑 Key Concepts & Definitions

• Null hypothesis stance: A null hypothesis stance states a default claim that there is no effect to compare against.
• Rejection of the null: Rejecting the null means choosing to abandon the no-effect stance based on the test outcome.
• True positive: A true positive is a decision that matches the presence of the effect when the study finds an effect.
• True negative: A true negative is a decision that matches the absence of the effect when the study does not find an effect.

📝 Essential Points

• Frequentist statistical tests evaluate the NULL stance, which claims there is no effect to find.
• Rejecting the null corresponds to concluding there is an effect rather than accepting the no-effect stance.
• Correct outcomes occur as true positives when an effect exists and as true negatives when no effect exists.
• The “cat” logic maps study findings to the four outcomes: true/false positives and true/false negatives.

💡 Memory Hook

Think four boxes: Effect or No effect × Found or Not found.