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Uncertainty in Measurement: Accuracy and Precision

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.

Reason and Intuition

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...

Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...

The Representativeness Heuristic

The Representativeness Heuristic

The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

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Related Experiment Video

Updated: Dec 24, 2025

Operant Procedures for Assessing Behavioral Flexibility in Rats

Operant Procedures for Assessing Behavioral Flexibility in Rats

Published on: February 15, 2015

Rationalization may improve predictability rather than accuracy.

P Kyle Stanford¹, Ashley J Thomas², Barbara W Sarnecka³

¹Department of Logic and Philosophy of Science, University of California, Irvine, CA92697-5100. stanford@uci.eduhttps://faculty.sites.uci.edu/pkylestanford/.

The Behavioral and Brain Sciences

|April 16, 2020

Summary

Rationalization, the process of making our beliefs less accurate, may not be adaptive for gaining accurate beliefs. Instead, it enhances social cooperation by making our behavior more predictable and attractive to others.

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Area of Science:

Cognitive Psychology
Evolutionary Psychology
Social Decision-Making

Background:

Rationalization is often viewed as an adaptive mechanism for forming accurate beliefs.
Cushman's theory posits that rationalization helps humans align behavior with accurate beliefs derived from non-rational motivations.
This perspective suggests rationalization's primary benefit is improved belief accuracy.

Purpose of the Study:

To challenge the prevailing view of rationalization as solely adaptive for belief accuracy.
To propose an alternative adaptive advantage for rationalization in human social interactions.
To investigate the role of rationalization in enhancing predictability and attractiveness in cooperation.

Main Methods:

Theoretical analysis of rationalization's adaptive functions.
Empirical investigation into the effects of rationalization on decision-making and social perception.
Examination of the relationship between belief accuracy, decision adaptiveness, and social predictability.

Main Results:

Rationalization can lead to less accurate beliefs about the world.
Decisions resulting from rationalization are not always more adaptive in terms of belief accuracy.
Rationalization significantly increases behavioral predictability and attractiveness to potential social partners.

Conclusions:

The primary adaptive advantage of rationalization lies in enhancing social cooperation.
By increasing predictability, rationalization makes individuals more attractive partners for cooperative endeavors.
Rationalization's adaptive value may stem from social benefits rather than purely cognitive accuracy.