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Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

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.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Random and Systematic Errors01:20

Random and Systematic Errors

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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Related Experiment Video

Updated: May 28, 2026

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Pitfalls and Inherent Biases in Liquid Handling Robotics: Investigations in Automation for SI Traceable Measurements.

Tabatha Hambidge1,2, Steven Corless1, Simon Cowen1

  • 1NML, LGC, The Priestley Centre, Guildford GU2 7XY, U.K.

Analytical Chemistry
|May 26, 2026
PubMed
Summary

Automated sample preparation using liquid handling robotics significantly improved accuracy for multianalyte quantification, reducing bias from 10% to <3.5%. This optimized workflow saves considerable analyst time while maintaining high precision.

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Area of Science:

  • Analytical Chemistry
  • Laboratory Automation

Background:

  • Industries like pharmaceuticals and clinical research increasingly use automated sample preparation for efficiency.
  • Robotics in analytical methods necessitates rigorous evaluation of workflows and apparatus for accuracy.

Purpose of the Study:

  • To investigate the accuracy and precision of an automated liquid handling workflow for multianalyte quantification.
  • To compare the performance of automated sample preparation with traditional manual methods using isotope dilution mass spectrometry.

Main Methods:

  • Optimized liquid handling parameters (e.g., syringe speeds) and physical setup (e.g., syringe tip, vial size).
  • Compared automated preparation to manual gravimetric preparation using double exact matching isotope dilution mass spectrometry (DEM-IDMS).
  • Assessed accuracy using NIST SRM 2389a amino acids in 0.1 mol/L HCl.

Main Results:

  • Systematic bias in the robotic workflow was reduced from 10% to <3.5% after optimization.
  • Achieved measurement uncertainty (≤5.3%) comparable to manual preparation.
  • Automated preparation saved approximately 6 hours of analyst time per sample set.

Conclusions:

  • Optimized automated sample preparation offers a viable alternative to manual methods for high-accuracy quantification.
  • The study highlights the advantages and challenges of robotic sample preparation in analytical laboratories.
  • Further understanding of automated workflows is crucial for advancing laboratory efficiency and data reliability.