CompTIA Data+ (DA0-002)Data AnalysisMedium
A data analyst is evaluating the effectiveness of a new customer service training program. They collect customer satisfaction scores (on a scale of 1 to 10) from two groups: one group whose representatives underwent the new training and another group whose representatives did not. The analyst wants to determine if there is a statistically significant difference in satisfaction scores between the two groups, assuming the data is not normally distributed and the sample sizes are small. Which statistical test should the analyst use?
- AChi-square test
- BMann-Whitney U test
- CANOVA
- DPaired t-test
Show answer & explanationAnswer & explanation
Correct answer: B. Mann-Whitney U test
The Mann-Whitney U test is appropriate for comparing two independent groups when the data is ordinal or not normally distributed, and the sample sizes are small. In this scenario, customer satisfaction scores are ordinal, and the assumption of normality is not met.
Why the other options are wrong
- A. The Chi-square test is used for categorical data, not ordinal scores.
- C. ANOVA is used for comparing means of three or more groups, or two groups if data is normally distributed.
- D. A paired t-test is used for dependent samples, not independent groups.
Mann-Whitney U Test
A non-parametric statistical hypothesis test used to compare the distributions of two independent samples to determine if they are significantly different.
- Used for ordinal or non-normally distributed interval/ratio data.
- Compares two independent groups.
- A non-parametric alternative to the independent samples t-test.
Memory trick: Mann-Whitney helps when data is not normal, like two different teams playing at different skill levels.