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Decision Making

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...

Decision Making: P-value Method

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...

Decision Making: Traditional Method

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...

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...

Uncertainty: Overview

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

Frustration and Conflict: Avoidance-Avoidance, Double-Approach Avoidance

Frustration and Conflict: Avoidance-Avoidance, Double-Approach Avoidance

Avoidance-avoidance conflict refers to a psychological situation where a person must choose between two or more unpleasant alternatives. These conflicts are particularly stressful because neither option is desirable. This dilemma is often expressed in sayings like "caught between a rock and a hard place" or "between the devil and the deep blue sea." For instance, individuals who fear dental procedures may find themselves torn between enduring a painful toothache or facing the...

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Related Experiment Video

Updated: Nov 24, 2025

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Decision-making with uncertainty.

Peter J Diggle¹, Tim Gowers², Frank Kelly³

¹Distinguished university professor of statistics in CHICAS, Lancaster Medical School, Lancaster University.

Significance (Oxford, England)

|December 28, 2020

Summary

Making good decisions during emergencies like the coronavirus pandemic is possible with risk-benefit analysis, even with limited information. This approach aids rapid decision-making when data is incomplete.

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Area of Science:

Decision Science
Risk Management
Epidemiology

Background:

Emergency situations, such as pandemics, necessitate rapid decision-making.
Decisions are often made with incomplete or uncertain information.

Purpose of the Study:

To explore the utility of risk-benefit analysis in emergency decision-making.
To demonstrate that sound judgments can be achieved despite data limitations.

Main Methods:

Application of risk-benefit analysis frameworks.
Evaluation of decision-making under uncertainty.

Main Results:

Risk-benefit analysis provides a structured approach to evaluating options.
This method facilitates effective decision-making even with partial information.

Conclusions:

Risk-benefit analysis is a valuable tool for navigating complex emergency scenarios.
Incomplete information does not preclude good decision-making in crises.