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Sources and Types of Errors

Chemical analysis encounters numerous uncertainties that make way for a host of 'errors', which can be categorized into systematic & random errors.
Chemical analysis usually encounters numerous uncertainties that make way for a host of 'errors', which can be broadly categorized into two categories:
1. Determinate (systematic) errors
2. Indeterminate (random) data.

However, it is pertinent to emphasize here that it is somewhat problematic at times to categorize an individual 'error' into one of the above-mentioned categories; nonetheless, classification is useful in studying various analytical errors that crop up during routine analyses.

1. Determinate (systemic) errors
Certain types of errors may have an identifiable value along with an easily assignable cause; however, in practice, these easily avoidable mistakes can be measured and accounted for with the use of conventional methods. Among the most important errors of this type are the following:

Personal errors - There are two main types of errors: personal and methodological. These errors are completely due to the analyst's human error and have nothing to do with the prescribed procedure or methodology.

Instrumental errors - Quite often, instruments need calibration and are not accurate and accurate. The pH meter, single pan electric balance, UV spectrophotometer, and potentiometers are examples of these assessment instruments.

Reagent errors - These errors are the results of the reagent itself, such as impurities inherent to the reagent, platinum (Pt) volatilization due to high temperatures, or unwanted foreign substances introduced by reagents when they react with porcelain and glass apparatus.

Constant errors - About error associated with constants, we have found that magnitude and error are relatively independent, with the magnitude of error decreasing as the measurement is larger.

Proportional errors - No matter how many samples are taken, the absolute error value remains constant regardless of that change. These materials tend to be incorporated into substances that interfere directly with the analytical process.

Errors due to methodology - A methodological error consists of a poor sample selection and an incomplete reaction. An error can be classified into one of three categories, such as - Errors that are related to system, random, and blunders. Errors committed by systematic means can be avoided in principle because they are caused by certain causes. In principle, systematic errors can be eliminated, because they have certain causes.

2. Intermediate (random) errors
Indeterminate errors cannot be attributed to any specific well-defined cause. Most of the time, they arise from the minute variations that may occur in successive measurements made by the same analyst, under almost identical conditions, although with utmost care. As a result, they cannot be corrected or eliminated, therefore, determining the 'ultimate limitation' on the specific measurements. Statistical treatment of the results of repeated measurement of the same variable has the positive effect of reducing a significant amount of the variables' importance when they are afterward analyzed.

Indeterminate errors: some factors to consider
Indeterminate errors have several salient features, including:
  1. The multiple measures of the same variable and subsequent refinement to such an extent that any agreement between replicates of the same variable is simply a coincidence,
  2. In addition to unpredictable and imperceptible factors affecting the results that usually make them appear as 'random fluctuations', there are many other factors that determine the results.
  3. Understanding the existence of specific definite variables which lie just outside our ability to control, such as temperature variations, noises and drifts from electronic circuits, and vibrations resulting from heavy traffic on a building, but are extremely close to its performance limit.
  4. By contrast, a variation that may appear random to a slipshod analyst can appear quite evident to a careful observer and even be quite manageable, if the observer pays close attention to the particular situation.
  5. In addition, the average of a large number of fine observations with random scatter is considerably more accurate, precise, and cogent than the average of the small number of coarse observations that appear perfectly aligned.
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Ankur Choudhary is India's first professional pharmaceutical blogger, author and founder of pharmaguideline.com, a widely-read pharmaceutical blog since 2008. Sign-up for the free email updates for your daily dose of pharmaceutical tips.
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