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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

190
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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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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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Range00:59

Range

12.0K
The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
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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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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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Costs, Value, and Variation.

Matthew A Pappas1, Hannah K Bassett2, Amit Pahwa3

  • 1Cleveland Clinic, Center for Value-based Care Research, Cleveland, OH, USA; Department of Hospital Medicine, Cleveland Clinic, Cleveland, OH, USA; Cleveland Clinic Lerner College of Medicine of Case Western University, Cleveland, OH, USA.

The Medical Clinics of North America
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PubMed
Summary
This summary is machine-generated.

Estimating healthcare costs and benefits is challenging due to imprecise data and modest medical service impacts. Understanding variation in medical practice is key for quality improvement initiatives.

Keywords:
Costs and cost analysisHealth care costsSmall-area analysisValue-based purchasing

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Area of Science:

  • Health Economics
  • Medical Practice Analysis

Background:

  • Healthcare cost estimation faces challenges with fixed and indirect costs.
  • Quantifying the benefits of medical services, including mortality reduction and quality of life improvements, is inherently imprecise.
  • Medical practice exhibits inherent variation due to scientific uncertainty, practitioner skill, and complex systems.

Purpose of the Study:

  • To explore the inherent imprecision in estimating healthcare costs and benefits.
  • To identify the sources of variation within medical practice.
  • To highlight the utility of understanding variation for quality improvement.

Main Methods:

  • Qualitative analysis of cost attribution challenges (direct vs. indirect/fixed costs).
  • Assessment of benefit estimation difficulties (mortality, quality of life).
  • Exploration of factors contributing to variation in medical practice.

Main Results:

  • Direct variable costs are easier to track than fixed and indirect costs.
  • The impact of most medical services on mortality is modest, and quality-of-life improvements are hard to quantify.
  • Variation in medical practice stems from evidence uncertainty, practitioner limitations, and systemic factors.

Conclusions:

  • Accurate estimation of healthcare service benefits and costs is difficult.
  • Understanding the sources of variation in medical practice is crucial for guiding quality improvement efforts.