Before calculating the average, which exploration technique should have been considered?

• A. Duplication
• B. Redundancy
• C. Binning
• D. Grouping

Answer: (A)

Before calculating an average, you should examine the data for duplicates. Duplicate records count more than once, which can pull the mean toward those repeated values and create a biased estimate of the central tendency. In data exploration, identifying and addressing duplicates is a key step: detect identical rows or repeated observations tied to the same entity, then remove or consolidate them so each entity is represented once. Once duplicates are handled, the average will reflect the true central tendency of the unique observations.

Other techniques like binning or grouping are useful for understanding how data is distributed or for computing averages within categories, but they don’t address the risk of overcounting that duplicates introduce before computing the overall average. Redundancy touches on having multiple copies for reliability, but the specific pre-average step you’d focus on is deduplication to ensure accurate averaging.