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Related Concept Videos

Real Number Operations01:27

Real Number Operations

The concept of real numbers includes all the values that can be represented on a continuous number line. The system began with basic counting values used for enumeration. It later expanded to include values that represent the absence of quantity and opposites of the counting values. When situations required expressing parts of a whole or dividing quantities evenly, values capable of representing such proportions were developed. When written using decimal notation, these values can end or repeat...
Arithmetic Sequences01:30

Arithmetic Sequences

An arithmetic sequence is a structured arrangement of numbers where each term is derived by adding a constant value, known as the common difference, to the previous term. This consistent pattern allows for the efficient computation of any term within the sequence as well as the cumulative sum of multiple terms. The formula for finding the nth term of an arithmetic sequence is:Here, aₙ represents the nth term of the sequence, a is the first term, d is the common difference, and n is the term...
Numerical Calculations01:24

Numerical Calculations

In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
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Harmonic Mean01:09

Harmonic Mean

The arithmetic mean is usually skewed towards the larger values in the data set. Therefore, to avoid this inherent bias towards smaller values, the harmonic mean is used.
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Arithmetic Mean01:08

Arithmetic Mean

The arithmetic mean is the most commonly used measure of the central tendency of a data set. It is defined as the sum of all the elements constituting the data set, divided by the total number of elements. It is sometimes loosely referred to as the “average.”
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Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
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Related Experiment Video

Updated: May 30, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Arithmetic mismatch negativity and numerical magnitude processing in number matching.

Yi-Fang Hsu1, Dénes Szücs

  • 1Centre for Neuroscience in Education, Department of Experimental Psychology, University of Cambridge, Downing site, Cambridge CB2 3EB, UK.

BMC Neuroscience
|August 13, 2011
PubMed
Summary

The arithmetic mismatch negativity (AMN) is triggered by violated expectations, not just numerical incongruity. The numerical distance effect can occur separately from the AMN, suggesting distinct cognitive processes.

Related Experiment Videos

Last Updated: May 30, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Area of Science:

  • Cognitive Neuroscience
  • Psychology

Background:

  • Investigated the link between arithmetic mismatch negativity (AMN) and semantic evaluation of numerical magnitude.
  • Explored whether AMN responds to numerical incongruity or violated strategic expectations.
  • Examined if the numerical distance effect is independent of AMN.

Purpose of the Study:

  • Determine the primary driver of AMN: numerical incongruity or violated expectations.
  • Ascertain the relationship between the numerical distance effect and AMN.
  • Clarify the neural underpinnings of numerical processing.

Main Methods:

  • Recorded event-related potentials (ERPs) during a digit matching task.
  • Manipulated trial frequency to elicit AMN.
  • Analyzed ERPs for the presence of AMN and numerical distance effect.

Main Results:

  • AMN was significantly enhanced for infrequent matching trials compared to frequent non-matching trials.
  • The numerical distance effect was observed over posterior scalp sites between 236-328 ms.
  • The numerical distance effect was found to be independent of the AMN.

Conclusions:

  • AMN is elicited by the violation of strategic expectations, not solely by numerical incongruity.
  • The numerical distance effect may be temporally associated with AMN but is not an integral component of it.
  • Suggests distinct neural mechanisms for expectation violation and magnitude processing.