Table of Contents
Introduction
Measurement error is the difference between a measured quantity and its real value (also known as observational error). It encompasses both random and systematic error (errors that occur spontaneously in all experiments) (caused by a miscalibrated instrument that affects all measurements).
Consider the case below: You’re balancing the weight of 100 marathon runners. Your scale is one pound off: this is a systemic error that will result in one pound off bodyweight calculations for all athletes. Some folks may be carrying a 2 oz. candy bar in their pockets or wearing wetter (and hence heavier) clothes. Because these are random problems, this is to be expected. Random mistakes will occur in all collected samples; they are unavoidable for the most part.
Various Error Metrics
Among the several error measurements are:
- The level of mistake in your measurement is referred to as absolute error. If you stand on a scale and it indicates 150 pounds but you know your exact weight is 145 pounds, the scale has an absolute error of 150 pounds – 145 pounds = 5 pounds.
- One-half of the measurement unit is the greatest possible error. When using a ruler that measures in whole yards (rather than fractions), the maximum you may go wrong is the one-half yard.
- Instrument Error: An incorrect instrument causes an error (like a scale that is off or a poorly worded questionnaire).
- Measurement Location Error: occurs when an instrument is placed in an inappropriate location, such as a thermometer left in direct sunlight.
- Operator Error: human factors that produce errors, such as inaccurately reading a scale.
Measuring Error Reduction Methods
- Examine your formulas to ensure that they are correct.
- Double-check all measures for accuracy. For example, on two worksheets, double-enter all entries and compare them.
- Make sure that all observers and measurement takers have been properly trained.
- Use the most exact instrument available to take the measurement.
- Measurements should be made in a controlled environment.
- Start with a small scale to test your measurement devices. For instance, create a focus group and ask how easy or difficult the questions were to understand.
- Use different metrics for the same construct. Use two different questionnaires if you’re looking to test for depression, for example.
Statistical Methods for Evaluating Measurement Error
The methods below are used to determine “absolute reliability”:
- The standard error of measurement (SEM) describes how the true score is estimated from repeated measurements done on the same instrument.
- A measure of the variability of a distribution of repeated scores or measurements is the coefficient of variation (CV). Smaller values indicate less fluctuation, resulting in values that are closer to the genuine score.
- Limits of agreement (LOA): provides an estimate of the range within which a part of the differences between measurements can be found.
FAQs
What is Measurement Error, and how does it affect you?
The discrepancy between the true or actual value and the measured value is known as measurement error. The precise value is measured, whereas the true value is the average of an infinite number of measurements.
Q: What are the many sorts of measuring errors?
Ans: The following three types of measurement errors can be identified.
Errors of this magnitude.
Errors that occur at random.
Errors that occur on a regular basis.
Q: What are some methods for avoiding measurement errors?
Ans:
- Measurement Error: How to Minimize It
- All measurements should be double-checked for precision.
- Make sure your formulas are right by double-checking them.
- Ascertain that all observers and measurement takers have received adequate training.
- Measure with the most precise device available.
- Under controlled conditions, take the measurements.
