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Related Concept Videos

What is Variation?01:14

What is Variation?

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
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Variation01:19

Variation

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An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
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Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Variation of Atmospheric Pressure01:18

Variation of Atmospheric Pressure

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Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Coefficient of Variation01:10

Coefficient of Variation

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The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
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New Variations for Strategy Set-shifting in the Rat
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Variation in Variation Measurement: A Mapping Review of Methods to Study Clinical Variation.

Amity E Quinn1,2,3, Jason E Black1,3, Derek Chew1,4,5

  • 1Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Journal of Evaluation in Clinical Practice
|January 22, 2026
PubMed
Summary
This summary is machine-generated.

Understanding clinical variation is key to improving healthcare value. This review found that current methods often identify variation but struggle to quantify or explain its sources, highlighting a need for better measurement approaches.

Keywords:
clinical variationfunnel plotshealth system performancemapping reviewmedical practice variationmethodsmultilevel models

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Area of Science:

  • Health Services Research
  • Clinical Epidemiology
  • Healthcare Quality Improvement

Background:

  • Healthcare delivery exhibits variation across providers, practices, and systems.
  • Understanding clinical variation is crucial for identifying overuse of low-value care and underuse of high-value care.
  • Existing methods for describing and quantifying clinical variation are inconsistently applied.

Purpose of the Study:

  • To systematically identify and characterize methods used to describe and quantify clinical variation in health care.
  • To map the landscape of methodologies applied to the study of clinical variation.
  • To inform improvements in measuring healthcare variation.

Main Methods:

  • A mapping review systematically searched health care and health services literature for studies on clinical variation.
  • Keyword analysis was used to identify graphical and statistical methods, specialties, settings, and performance areas.
  • Included studies measured care processes or health outcomes at the person-level or higher using routinely collected data.

Main Results:

  • Over 6,000 studies were analyzed, with most employing basic methods like regression or crude comparisons.
  • Fewer than 1,000 studies utilized advanced multilevel models to quantify variation.
  • Multilevel models were infrequently applied to the study of health care quality variation.

Conclusions:

  • Current methods for studying clinical variation primarily identify its existence rather than quantifying or explaining its underlying causes.
  • This review provides insights into the scope and application of existing methods for measuring variation.
  • Improved measurement of clinical variation is essential for enhancing healthcare value and equity.