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Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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.
Mean Absolute Deviation01:13

Mean Absolute Deviation

The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
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...
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 8, 2026

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
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Absolute error.

R W Schutz1

  • 1a School of Physical Education and Recreation , University of British Columbia.

Journal of Motor Behavior
|August 22, 2013
PubMed
Summary
This summary is machine-generated.

Composite error scores are not valid indicators of motor performance. Henry's E(2) statistic shares the same flaws as A(2), making it equally unreliable for assessing motor skills.

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Area of Science:

  • Motor Control
  • Biomechanics
  • Human Performance

Background:

  • Composite error scores are frequently used to evaluate motor performance.
  • Previous research has questioned the interpretability and validity of these composite scores.
  • The A(2) statistic has been identified as a potentially flawed measure in this context.

Purpose of the Study:

  • To support and expand the position that composite error scores are not interpretable indicators of motor performance.
  • To critically evaluate Henry's E(2) statistic in comparison to the A(2) statistic.
  • To address specific criticisms raised by Henry regarding the Schutz and Roy paper.

Main Methods:

  • Statistical analysis of motor performance data.
  • Comparative evaluation of different error scoring methods, specifically A(2) and E(2) statistics.
  • Theoretical critique and response to existing literature and criticisms.

Main Results:

  • The study supports the argument that composite error scores lack interpretability for motor performance assessment.
  • Henry's E(2) statistic was found to possess similar deficiencies to the A(2) statistic.
  • The E(2) statistic is therefore considered equally invalid as an indicator of motor performance.

Conclusions:

  • Composite error scores, including Henry's E(2) statistic, are not valid or interpretable measures of motor performance.
  • The findings challenge the utility of these statistical approaches in motor control research.
  • Further research is needed to develop more robust methods for quantifying motor performance.