Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
Random Sampling Method01:09

Random Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Looking behind: Turning cards in the selection task.

Quarterly journal of experimental psychology (2006)·2021
Same author

John A. Swets (1928-2016).

The American psychologist·2017
Same author

Are Social Scientists Harder on Their Colleagues Than Physical Scientists Were on Theirs in the Past? Commentary on Trafimow & Rice (2009).

Perspectives on psychological science : a journal of the Association for Psychological Science·2015
Same author

Knowledge assessment: Squeezing information from multiple-choice testing.

Journal of experimental psychology. Applied·2015
Same author

Roles of human factors and ergonomics in meeting the challenge of terrorism.

The American psychologist·2011
Same author

Five down, Absquatulated: crossword puzzle clues to how the mind works.

Psychonomic bulletin & review·2011
Same journal

Attributing social meaning to animated shapes: A new experimental study of apparent behavior.

The American journal of psychology·2021
Same journal

Scientific Study of Magic: Binet's Pioneering Approach Based on Observations and Chronophotography.

The American journal of psychology·2018
Same journal

Child and Ancient Man: How to Define Their Commonalities and Differences.

The American journal of psychology·2018
Same journal

Adolescent Aggression as Predicted from Parent-Child Relationships and Executive Functions.

The American journal of psychology·2018
Same journal

The Effect of Collective Transitions on the Organization and Contents of Autobiographical Memory: A Transition Theory Perspective.

The American journal of psychology·2018
Same journal

The Development and Validity of a Chinese Version of the Compound Remote Associates Test.

The American journal of psychology·2018
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
12:36

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Published on: May 9, 2011

On producing random binary sequences.

Raymond S Nickerson1, Susan F Butler

  • 1Tufts University, USA. r.nickerson@tufts.edu

The American Journal of Psychology
|June 11, 2009
PubMed
Summary
This summary is machine-generated.

People struggle to generate random binary sequences, performing poorly on tasks simulating coin tosses. While their sequences share some statistical similarities with random ones, common biases like the gambler's fallacy were not observed.

More Related Videos

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
11:34

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Published on: August 9, 2019

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
09:40

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

Published on: November 15, 2014

Related Experiment Videos

Last Updated: Jun 22, 2026

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
12:36

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Published on: May 9, 2011

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
11:34

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Published on: August 9, 2019

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
09:40

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

Published on: November 15, 2014

Area of Science:

  • Cognitive Psychology
  • Behavioral Science
  • Human-Computer Interaction

Background:

  • Researchers widely believe humans are inept at generating truly random binary sequences.
  • Previous studies suggest cognitive biases influence perceived randomness in human-generated sequences.
  • Understanding these limitations is crucial for applications requiring random number generation.

Purpose of the Study:

  • To investigate the accuracy of human-generated random binary sequences.
  • To determine if participants' sequences are statistically indistinguishable from chance.
  • To examine the prevalence of common biases, such as the gambler's fallacy, in sequence generation.

Main Methods:

  • Participants were tasked with creating sequences of binary outcomes (e.g., coin tosses).
  • The generated sequences were statistically analyzed against expected random distributions.
  • Specific biases, including alternation and repetition patterns, were assessed.

Main Results:

  • Participants' ability to produce statistically random sequences was generally poor.
  • However, the distributional properties of generated sequences were qualitatively similar to random processes.
  • Contrary to common findings, excessive alternations, fewer repetitions, and the gambler's fallacy were not consistently observed.

Conclusions:

  • Human performance in generating random binary sequences is limited.
  • While not perfectly random, generated sequences exhibit some characteristics of randomness.
  • The study did not find strong evidence for typical cognitive biases in this specific task.