AWS Certified Machine Learning – SpecialtyExploratory Data AnalysisEasy
A financial institution is analyzing credit card transaction data to detect fraudulent activities. They are particularly interested in understanding the distribution of transaction amounts. The data shows a heavily right-skewed distribution with a long tail of very large transactions. Which statistical measure of central tendency would be least affected by these extreme values and best represent the 'typical' transaction amount?
- AGeometric Mean
- BMode
- CMean
- DMedian
Show answer & explanationAnswer & explanation
Correct answer: D. Median
For heavily skewed distributions with outliers, the median is the most robust measure of central tendency because it is not influenced by extreme values, unlike the mean. The mean would be pulled towards the long tail of large transactions.
Why the other options are wrong
- A. The geometric mean is used for data that grows exponentially, not for robustness to outliers in skewed financial data.
- B. The mode represents the most frequent value, which might not be central in skewed data.
- C. The mean is highly sensitive to outliers and skewed data.
Median Robustness
The median is a measure of central tendency that is robust to outliers and skewed distributions, as it represents the middle value in an ordered dataset.
- Not affected by extreme values.
- Useful for skewed data where the mean is misleading.
- Calculated by ordering data and finding the middle point.
Memory trick: Median is the middle, mean is the average, mode is the most.