Bias

Bias

In statistics and data analysis, bias signifies a systematic error that potentially impinges upon the precision and representativeness of data, estimates, or derived conclusions. Bias can insinuate itself at diverse phases of research or analysis - data collection, sampling, measurement, or interpretation - instigating outcomes that may be deceptive or imprecise.

Types of Bias

Bias manifests itself in an array of forms, encapsulating:
Selection bias: Selection bias emerges when a study's sample fails to reflect the broader population accurately, culminating in skewed results.
Measurement bias: This variant of bias springs from errors committed during data collection, measurement, or recording, engendering systematic discrepancies in the data.
Confirmation bias: As a cognitive bias, confirmation bias points to individuals' propensity to interpret, pursue, or recall information aligning with their pre-existing beliefs or expectations.
Response bias: Response bias transpires when study participants offer inaccurate or dishonest responses, deliberately or inadvertently, thus warping the study's conclusions.
Updated: May 22, 2023 | Published by: Statistico | About Us | Data sources
Cricket: Highest ODI Scores, by player
Cricket: Highest ODI Scores, by player
Sachin Tendulkar, Virender Sehwag, Chris Gayle, and Rohit Sharma are some of the players in cricket history who have scored highest runs in an ODI match, with Sharma holding the top spot with his colossal... Read more »
All topics
Labor Market
The Labor Market refers to the supply and demand dynamics of labor where employers seek the best workers for their needs and job seekers look for the best job opportunities. Read more »