What is a Parametric Statistical Test?

📚 Quick Study Guide

• 📐 Parametric statistical tests rely on assumptions about the distribution of the population from which the sample is taken.
• 🔢 These tests are typically used when the data is normally distributed or approximately so.
• 📊 Common parametric tests include the t-test, ANOVA, and Pearson correlation.
• 🧪 These tests analyze means, variances, and standard deviations.
• 📝 Key assumptions include: data is normally distributed, variances are equal (homogeneity of variance), and data is independent.
• 📈 Violation of assumptions can lead to inaccurate results.
• 💡 Parametric tests are generally more powerful than non-parametric tests when their assumptions are met.

Practice Quiz

1. Which of the following is a key assumption of parametric statistical tests?
   1. Data is skewed.
   2. Data is normally distributed.
   3. Variances are unequal.
   4. Data is dependent.
2. Which of the following is a common parametric statistical test?
   1. Chi-square test
   2. Mann-Whitney U test
   3. t-test
   4. Kruskal-Wallis test
3. What does homogeneity of variance mean?
   1. Variances are equal across groups.
   2. Variances are unequal across groups.
   3. Data is normally distributed.
   4. Data is skewed.
4. What type of data is suitable for parametric tests?
   1. Nominal data
   2. Ordinal data
   3. Interval or ratio data
   4. Categorical data
5. What happens if the assumptions of a parametric test are severely violated?
   1. The results are always accurate.
   2. The results may be inaccurate.
   3. The test automatically corrects for violations.
   4. The sample size is irrelevant.
6. Which of the following is analyzed in parametric tests?
   1. Medians
   2. Ranks
   3. Means
   4. Frequencies
7. Which test is used to compare the means of three or more groups?
   1. t-test
   2. ANOVA
   3. Chi-square test
   4. Correlation test