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Measurement errors can be divided into two components: ... The term "observational error" is also sometimes used to refer to response errors and some other types of ...
The late 20th century also saw an expansion of the application of analytical chemistry from somewhat academic chemical questions to forensic, environmental, industrial and medical questions, such as in histology. [6] Modern analytical chemistry is dominated by instrumental analysis. Many analytical chemists focus on a single type of instrument.
Laboratory quality control is designed to detect, reduce, and correct deficiencies in a laboratory's internal analytical process prior to the release of patient results, in order to improve the quality of the results reported by the laboratory. Quality control (QC) is a measure of precision, or how well the measurement system reproduces the ...
Titration. A burette and Erlenmeyer flask (conical flask) being used for an acid–base titration. Titration (also known as titrimetry[ 1] and volumetric analysis) is a common laboratory method of quantitative chemical analysis to determine the concentration of an identified analyte (a substance to be analyzed).
The range in amount of possible random errors is sometimes referred to as the precision. Random errors may arise because of the design of the instrument. In particular they may be subdivided between errors in the amount shown on the display, and; how accurately the display can actually be read.
In analytical chemistry, a calibration curve, also known as a standard curve, is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration. [ 1] A calibration curve is one approach to the problem of instrument calibration; other standard ...
Type I and type II errors. In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example, an innocent person may be convicted. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false.
Accuracy measures how close a given set of observations are to their true value. Precision measures how close the observations are to each other. Accuracy and precision of observations lying on a bell curve. In the language of statistics: Accuracy is a description of systematic errors, a measure of bias. Precision is a description of random ...