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

5-Number Summary01:04

5-Number Summary

5.1K
In a dataset, the 5-number summary includes the minimum data value, the data value of the first quartile, the median data value or data value of the second quartile, the data value of the third quartile, and the maximum data value. These 5 data values can be visualized as a box and whisker plot.
In a box plot, the minimum and maximum data values represent the lower and upper whiskers in the graph, and the median is designated as the center of the box in the chart. The first quartile and third...
5.1K
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

759
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...
759
Basic Discrete Time Signals01:16

Basic Discrete Time Signals

353
The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is...
353
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

349
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...
349
RNA-seq03:21

RNA-seq

10.5K
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...
10.5K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

33.0K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
33.0K

You might also read

Related Articles

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

Sort by
Same author

Overt Visual Attention in the Formation of Preference Between Complex Lottery Options.

Computational brain & behavior·2026
Same author

Stress-related hypofrontality in depression and its relation to altered activation prior to the stress response.

NeuroImage. Clinical·2026
Same author

Inter-brain coupling tracks emotional co-regulation.

Cognitive, affective & behavioral neuroscience·2026
Same author

Theta burst stimulation prior to stress exposure alters amplitude of low-frequency fluctuations.

Biological psychology·2026
Same author

Rumination Out Loud? Linguistic, Neural, and Psychophysiological Correlates of the Think-Aloud Paradigm.

Depression and anxiety·2026
Same author

[Scimitar Syndrome in a young adult with an arteriovenous fistula from the celiac trunk - A rare adult presentation].

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin·2026

Related Experiment Video

Updated: Oct 16, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

3.2K

Extracting Summary Statistics of Rapid Numerical Sequences.

David Rosenbaum1, Moshe Glickman2,3, Marius Usher1

  • 1School of Psychological Sciences, Tel-Aviv University, Tel Aviv, Israel.

Frontiers in Psychology
|October 18, 2021
PubMed
Summary

Participants can accurately estimate summary statistics from fast number sequences. Estimation precision for the sequence mean improves with sequence length, with a holistic strategy proving most efficient.

Keywords:
averagingcomputational modelingdecision makingnumerical cognitionpopulation codingsummary statistics

More Related Videos

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

10.4K
G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
06:40

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

5.9K

Related Experiment Videos

Last Updated: Oct 16, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

3.2K
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

10.4K
G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
06:40

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

5.9K

Area of Science:

  • Cognitive psychology
  • Numerical cognition
  • Decision-making

Background:

  • Human observers process rapid numerical sequences.
  • Extracting summary statistics like mean and variance is crucial for understanding numerical cognition.
  • The efficiency of different cognitive strategies for statistical estimation is not fully understood.

Purpose of the Study:

  • To investigate the human ability to extract summary statistics from rapid numerical sequences.
  • To determine how sequence length affects the precision of statistical estimations.
  • To identify and compare the cognitive strategies employed for estimating sequence statistics.

Main Methods:

  • Four experiments were conducted with 100 participants.
  • Participants viewed rapid sequences of two-digit numbers at a rate of 4/s.
  • Model selection was used to identify individual estimation strategies (holistic vs. rule-based).

Main Results:

  • Participants demonstrated a remarkable ability to extract summary statistics.
  • Estimation precision for the sequence mean increased with sequence length.
  • A holistic, frequency-based strategy was generally more precise than a rule-based strategy, especially when estimating both mean and variance.

Conclusions:

  • The human visual system can effectively extract summary statistics from rapid numerical streams.
  • A holistic processing strategy appears more efficient for numerical statistical estimation.
  • Findings have implications for understanding numerical processing pathways and decision-making under uncertainty.