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Related Concept Videos

Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the population that is...
First Derivative Test: Problem Solving01:25

First Derivative Test: Problem Solving

Imagine an asset price that crashes to a low point, rebounds sharply as bargain-hunters step in, and then gradually declines. Such behavior can be modeled with a smooth function whose turning points represent locally overvalued and undervalued regions. A convenient example that captures rebound followed by decay is:The high and low points of this curve are identified using the first derivative test, which determines where the function changes from increasing to decreasing or vice versa. To...
Factorial Design02:01

Factorial Design

Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
Bonferroni Test01:10

Bonferroni Test

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Related Experiment Video

Updated: Jun 3, 2026

Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

Delay discounting of different commodities II: confirmatory analyses.

Jeffrey N Weatherly1, Heather K Terrell

  • 1Department of Psychology, University of North Dakota, Grand Forks 58202-8380, USA. jeffrey.weatherly@und.edu

The Journal of General Psychology
|March 17, 2011
PubMed
Summary

Delay discounting, the choice of smaller immediate rewards over larger delayed ones, shows domain-specific patterns. How a choice is framed significantly impacts discounting behavior.

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Area of Science:

  • Behavioral Economics
  • Decision Science
  • Cognitive Psychology

Background:

  • Delay discounting describes the devaluation of rewards with increasing delays.
  • Prior research suggests discounting varies across different commodity domains.
  • This domain specificity implies decisions in one area may not predict decisions in another.

Purpose of the Study:

  • To investigate if delay discounting patterns are consistent across established commodity domains.
  • To examine the influence of commodity type and framing on delay discounting.
  • To validate previous findings on domain specificity and framing effects.

Main Methods:

  • 283 participants completed a delay-discounting task using commodity sets from prior research.
  • Confirmatory factor analysis was employed to assess the structure of discounting.
  • Commodities were presented in different frames to evaluate framing effects.

Main Results:

  • Confirmatory factor analyses supported the existence of distinct discounting domains.
  • Discounting rates varied significantly based on the type of commodity.
  • The framing of commodities demonstrably influenced participants' discounting behavior.

Conclusions:

  • Results strongly support the domain-specific nature of delay discounting.
  • Temporal decision-making for one set of consequences does not reliably predict decisions for others.
  • Framing effects can significantly alter observed discounting, complicating interpretation.