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Systematic Error: Methodological and Sampling Errors01:15

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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
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Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
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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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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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Minimizing and Reporting Momentary Time-Sampling Measurement Error in Single-Case Research.

Kathleen B Cook1,2, Sara M Snyder1,3

  • 11Department of Communication Sciences and Special Education, University of Georgia, Athens, GA USA.

Behavior Analysis in Practice
|April 2, 2020
PubMed
Summary

Momentary time sampling (MTS) minimizes behavior measurement error by considering behavior duration and interval length. This study details methods to monitor and report MTS measurement error in single-case research designs.

Keywords:
Interval recordingMeasurement errorMomentary time samplingSingle-case research design

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Area of Science:

  • Behavioral science
  • Research methodology
  • Applied behavior analysis

Background:

  • Momentary time sampling (MTS) is a widely used interval-measurement system for observing behavior duration.
  • Minimizing measurement error is crucial for the validity of MTS data.
  • Recent studies highlight the importance of behavior duration, interval length, and session length in reducing MTS error.

Purpose of the Study:

  • To describe practical steps for minimizing measurement error in MTS within a single-case design study.
  • To detail methods for monitoring and reporting MTS measurement error across different experimental conditions.
  • To provide a framework for enhancing the reliability of duration-based behavioral observations.

Main Methods:

  • Implementing specific procedures to reduce measurement error during momentary time sampling.
  • Calculating and analyzing duration per occurrence measurements intermittently.
  • Monitoring measurement error across various experimental conditions in a single-case design.

Main Results:

  • The described methods effectively minimized measurement error in the momentary time sampling system.
  • Continuous monitoring and analysis of duration per occurrence provided insights into measurement consistency.
  • Reliable MTS data were obtained across different experimental conditions.

Conclusions:

  • The proposed methodology offers a robust approach to minimize and monitor measurement error in momentary time sampling.
  • Adhering to these steps enhances the accuracy and trustworthiness of duration-based behavioral data in research.
  • This strategy is particularly valuable for single-case design research requiring precise behavioral measurement.