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Related Concept Videos

Variance01:15

Variance

13.3K
The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.The standard deviation measures the spread in the same units as the data.
13.3K
Variability: Analysis01:11

Variability: Analysis

777
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...
777
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

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A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
3.2K
Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

30.9K
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...
30.9K
Variation01:19

Variation

8.4K
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...
8.4K
Coefficient of Variation01:10

Coefficient of Variation

9.0K
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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Related Experiment Video

Updated: Apr 15, 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

Published on: October 11, 2018

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Variation reduction: what's old is new again.

Lawrence Shapiro

    The Journal of Medical Practice Management : MPM
    |March 27, 2015
    PubMed
    Summary
    This summary is machine-generated.

    Variation reduction empowers physicians with transparent clinical data, fostering discussions on the standard of care. This physician-led approach avoids top-down mandates, aiding accountable care organizations.

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    Area of Science:

    • Healthcare Management
    • Clinical Practice Improvement
    • Health Services Research

    Background:

    • Variation in clinical practice can impact patient outcomes and healthcare costs.
    • Developing successful Accountable Care Organizations (ACOs) requires effective strategies for quality improvement.
    • Physician engagement is crucial for successful healthcare initiatives.

    Purpose of the Study:

    • To describe the principles and benefits of variation reduction in clinical practice.
    • To highlight the role of transparent data in guiding physician decision-making.
    • To emphasize the physician-driven nature of variation reduction for ACO development.

    Main Methods:

    • Providing physicians with transparent data on their clinical practice patterns.
    • Facilitating discussions among physicians regarding the standard of care.
    • Allowing physicians to self-select topics for practice improvement initiatives.

    Main Results:

    • Physician-led topic selection promotes engagement and ownership.
    • Transparent data facilitates informed discussions on clinical standards.
    • Avoidance of top-down decision-making respects physician autonomy.

    Conclusions:

    • Variation reduction, driven by transparent data and physician choice, is a key strategy for ACO success.
    • This approach fosters a culture of continuous improvement and evidence-based practice.
    • Empowering physicians is essential for optimizing healthcare delivery and achieving organizational goals.