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Related Concept Videos

Standard Deviation01:10

Standard Deviation

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The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more...
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Self-Discrepancy and Its Effects01:29

Self-Discrepancy and Its Effects

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Self-discrepancy theory explains how people compare their actual self to their ideal and ought selves and how mismatches between these self-guides can lead to emotional distress. Developed by E. Tory Higgins, the theory distinguishes among three components of self-concept: the actual self, the ideal self, and the ought self. These refer respectively to how individuals perceive themselves, how they aspire to be, and how they believe they are obligated to be. Emotional well-being, self-esteem,...
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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...
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Empirical Method to Interpret Standard Deviation01:09

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The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
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Standard Solutions

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Standard solutions refer to solutions with a precisely known concentration or composition. A primary standard is a highly pure, high molar mass, stable substance that is entirely soluble in water, the most commonly used solvent in analytical chemistry. The primary standard solution can be used to standardize secondary standards, which are substances with known concentrations but are less pure and stable. Standard solutions are essential for achieving accurate and reliable results in analytical...
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Units and Standards of Measurement01:10

Units and Standards of Measurement

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A physical quantity is defined either by specifying its measurement method or by stating how it is calculated from other measurements. For example, consider a metallic cube. We might define its mass and dimensions by specifying methods for measuring them, such as using a weighing machine and a meter scale. Then, we could define the volume by stating that it is the cube of its side, and we could calculate the density as the mass divided by the volume.
Measurements of physical quantities are...
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Standardisation and Its Discontents.

Robert L Wears1

  • 1University of Florida, Jacksonville, FL 32209, USA / Imperial College, London, UK.

Cognition, Technology & Work (Online)
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Summary
This summary is machine-generated.

Healthcare standardization is complex, with both benefits and drawbacks. This analysis examines the multifaceted nature of standardization in Western healthcare systems to foster more productive discussions.

Keywords:
Taylorismcomplexityqualityresiliencesafetystandardisation

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Area of Science:

  • Healthcare quality and safety
  • Sociology of healthcare
  • Health policy analysis

Background:

  • Modern Western healthcare faces criticism regarding a lack of standardization.
  • Standardization is often proposed as a solution to quality and safety issues.
  • The concept of standardization in healthcare is complex and multifaceted.

Purpose of the Study:

  • To explore the complexities surrounding healthcare standardization.
  • To examine the advantages and disadvantages of healthcare standardization.
  • To analyze the political and sociological implications of standardization in healthcare.

Main Methods:

  • Literature review and critical analysis of existing discourse on healthcare standardization.
  • Exploration of theoretical frameworks related to standardization.
  • Case study examples (implied, not explicit in abstract).

Main Results:

  • Standardization in healthcare presents significant complexities beyond simple implementation.
  • Potential benefits include improved safety and efficiency, but risks of de-skilling and reduced innovation exist.
  • Sociopolitical factors heavily influence the adoption and impact of standardization.

Conclusions:

  • Discourses on healthcare standardization require a nuanced understanding of its complexities.
  • Addressing standardization requires considering its advantages, disadvantages, and sociopolitical context.
  • More fruitful discussions on standardization can lead to better healthcare quality and safety outcomes.