Parametric vs. Non-parametric tests: A comparison of underlying assumptions.

📚 Quick Study Guide

• 🔢 Parametric tests assume data follows a specific distribution (e.g., normal distribution).
• 📊 Non-parametric tests do not rely on specific distributional assumptions.
• 🧪 Parametric tests are more powerful when assumptions are met.
• 📈 Non-parametric tests are useful with ordinal or nominal data.
• 💡 Common parametric tests: t-tests, ANOVA.
• 🧮 Common non-parametric tests: Mann-Whitney U test, Kruskal-Wallis test.
• 📝 Key consideration: Data distribution and measurement scale.

Practice Quiz

1. Which of the following is an assumption of parametric tests?
   1. A) Data is normally distributed.
   2. B) Data is non-normally distributed.
   3. C) Data is ordinal.
   4. D) Data is nominal.


2. Which type of data is most suitable for non-parametric tests?
   1. A) Interval data
   2. B) Ratio data
   3. C) Nominal data
   4. D) Continuous data


3. Which of the following is a common parametric test?
   1. A) Mann-Whitney U test
   2. B) Kruskal-Wallis test
   3. C) t-test
   4. D) Chi-square test


4. Which of the following is a common non-parametric test?
   1. A) ANOVA
   2. B) Regression analysis
   3. C) t-test
   4. D) Wilcoxon signed-rank test


5. What is a primary advantage of using parametric tests when their assumptions are met?
   1. A) Simplicity
   2. B) Increased power
   3. C) Applicability to all data types
   4. D) Reduced computational complexity


6. When might you choose a non-parametric test over a parametric test?
   1. A) When data is normally distributed
   2. B) When sample size is very large
   3. C) When data violates parametric assumptions
   4. D) When you need to estimate population parameters


7. Which of the following best describes the key difference between parametric and non-parametric tests?
   1. A) Parametric tests are always more accurate.
   2. B) Non-parametric tests require larger sample sizes.
   3. C) Parametric tests make assumptions about the data distribution, while non-parametric tests do not.
   4. D) Non-parametric tests are only used for categorical data.