Outlayer

An outlayer is a term used in statistics and data analysis to refer to a data point that significantly differs from the rest of the dataset. Outlayers can indicate variability, measurement error, or novel phenomena, and they often require separate investigation or treatment in analyses to avoid skewing results.

Outlayer meaning with examples

In the recent study on environmental pollutants, one outlayer was found far above the expected concentration levels, raising concerns about potential environmental violations and prompting further investigation into industrial discharge practices.
While analyzing the test scores of the students, an outlayer appeared that prompted the educational researchers to explore the student's unique learning methods which significantly differed from their peers.
Statisticians often focus on outlayers when conducting regression analyses to determine if they are influencing the overall trend or if they represent an important anomaly worthy of further study.
During the population study, researchers encountered an outlayer in the data, which led them to re-evaluate their sampling methods and consider the possibility of rare demographic segments.
The financial analyst discovered an outlayer in quarterly earnings that did not align with the historical performance of the company, indicating a possible error in reporting or a significant change in market dynamics.

Outlayer Synonyms

aberration anomalous point anomaly deviation discrepancy exception fluke irregularity misalignment misfit oddity outcast outlier peculiarity quake rogue straggler strange occurrence uncommon instance variant

Outlayer Antonyms

average commonality conformity congruence consistency familiarity habit mean norm normalcy ordinariness pattern predictability regularity sameness similarity standard typical uniformity usuality