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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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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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Software-Assisted Quantitative Measurement of Osteoarthritic Subchondral Bone Thickness
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Intraobserver Error in Macromorphoscopic Trait Data,.

Kelly R Kamnikar1, Amber M Plemons1, Joseph T Hefner1

  • 1Department of Anthropology, Michigan State University, 655 Auditorium Drive, East Lansing, MI, 48824.

Journal of Forensic Sciences
|May 26, 2017
PubMed
Summary
This summary is machine-generated.

Forensic anthropologists

Keywords:
ancestryforensic anthropologyforensic sciencemacromorphoscopic traitsobserver experiencequantitative data analysis

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Area of Science:

  • Forensic Anthropology
  • Biological Anthropology

Background:

  • Macromorphoscopic traits are crucial for estimating ancestry from unidentified skeletal remains.
  • Quantifying observer error is essential for developing robust forensic databases.

Purpose of the Study:

  • To assess intraobserver error in macromorphoscopic trait analysis over a 14-year period.
  • To evaluate the impact of observer experience and technological advancements on data accuracy.

Main Methods:

  • A 14-year intraobserver error study (2002-2016) was conducted.
  • Ten macromorphoscopic traits were assessed to maximize sample comparisons.
  • Data collection methods and observer experience were analyzed for error patterns.

Main Results:

  • Three primary error patterns were identified: observer experience, new technologies, and inherent method error.
  • The study found that error effects on macromorphoscopic trait analysis are predictable.
  • Error did not significantly impact the overall utility of the method.

Conclusions:

  • Intraobserver error in macromorphoscopic analysis is quantifiable and predictable.
  • Despite potential error sources, macromorphoscopic traits remain a valuable tool in forensic anthropology.
  • Findings support the continued development of macromorphoscopic databases for ancestry estimation.