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Related Concept Videos

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Language01:16

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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
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Common Ion Effect03:24

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Compared with pure water, the solubility of an ionic compound is less in aqueous solutions containing a common ion (one also produced by dissolution of the ionic compound). This is an example of a phenomenon known as the common ion effect, which is a consequence of the law of mass action that may be explained using Le Châtelier’s principle. Consider the dissolution of silver iodide:
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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Related Experiment Video

Updated: Jan 27, 2026

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
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Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

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Common language effect size for correlations.

Xiaofeng Steven Liu1, Ryan Carlson1, Ken Kelley2

  • 1a University of South Carolina.

The Journal of General Psychology
|March 26, 2019
PubMed
Summary
This summary is machine-generated.

The Pearson correlation coefficient can be translated into a common language effect size. This makes correlation results understandable to everyone, illustrating the probability of one variable

Keywords:
Common language effect sizecorrelation

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Area of Science:

  • Statistics
  • Psychometrics
  • Data Analysis

Background:

  • The Pearson correlation coefficient (r) is widely used but often difficult for non-experts to interpret.
  • Understanding the practical significance of correlation strength is crucial in various scientific fields.

Purpose of the Study:

  • To introduce and demonstrate a common language effect size derived from the Pearson correlation coefficient.
  • To enhance the interpretability of correlation coefficients for a broader audience.

Main Methods:

  • Translating the Pearson correlation coefficient into a common language effect size.
  • Illustrating the application of this effect size with three distinct examples.

Main Results:

  • The common language effect size quantifies the probability of observing a certain value on one variable given a value on another.
  • This method provides an intuitive understanding of correlation strength, bridging the gap between statistical values and real-world implications.

Conclusions:

  • The common language effect size offers a more accessible interpretation of Pearson and multiple correlation coefficients.
  • This approach facilitates better communication of research findings to both academic and lay audiences.