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Related Concept Videos

Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Reliability and Validity01:29

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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Accuracy and Precision01:52

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
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Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Time to do something about reproducibility.

Sean J Morrison1

  • 1Sean J Morrisonis an Investigator of the Howard Hughes Medical Institute, and Director of the Children's Research Institute at the University of Texas Southwestern Medical Center, Dallas, USA. He is also the Mary McDermott Cook Chair in Pediatric Genetics and Director of the Hamon Laboratory for Stem Cells and Cancer at UTSW, and a Cancer Prevention and Research Institute of Texas Scholar sean.morrison@utsouthwestern.edu.

Elife
|December 11, 2014
PubMed
Summary
This summary is machine-generated.

Scientists, journals, and communities can improve the assessment of irreproducible results. Promoting good science and efficient self-correction are key to scientific integrity.

Keywords:
blood stem cellshuman biologymedicinemethodologyopen sciencereplicationreproducibilityreproducibility project: cancer biology

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Area of Science:

  • Reproducibility in scientific research
  • Scientific integrity and self-correction

Background:

  • Challenges in assessing and publishing irreproducible results.
  • Need for enhanced mechanisms for scientific community self-correction.

Discussion:

  • The role of individual scientists in promoting good science.
  • The collective responsibility of scientific communities in maintaining standards.
  • The critical function of scientific journals in vetting publications.

Key Insights:

  • Improving the evaluation of irreproducible research is crucial.
  • Fostering good scientific practices enhances research reliability.
  • Streamlining scientific self-correction accelerates progress.

Outlook:

  • Developing robust frameworks for assessing reproducibility.
  • Encouraging open science practices to improve transparency.
  • Strengthening the feedback loops within the scientific ecosystem.