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Analytical chemistry studies and uses instruments and methods to separate, identify, and quantify matter. [ 1] In practice, separation, identification or quantification may constitute the entire analysis or be combined with another method. Separation isolates analytes.
Ant on a rubber rope: An ant crawling on a rubber rope can reach the end even when the rope stretches much faster than the ant can crawl. Cramer's paradox: The number of points of intersection of two higher-order curves can be greater than the number of arbitrary points needed to define one such curve.
In statistical hypothesis testing, the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to ...
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.
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).
Traill (2008, espec.Table "S" on p.31) follows Jerne and Popper in seeing this strategy as probably underlying all knowledge-gathering systems — at least in their initial phase.
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.