Descriptive Business statistics are most often concerned with two sets of properties of a distribution : central tendency seeks to characterize the distribution's central or typical value, while dispersion characterizes the extent to which members of the distribution depart from its center and each other.
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Inferences on mathematical Business statistics are made under the framework of probability theory, which deals with the analysis of random phenomena.
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Some consider Business statistics to be a distinct mathematical science rather than a branch of mathematics.
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The scope of the discipline of Business statistics broadened in the early 19th century to include the collection and analysis of data in general.
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Today, statistics is widely employed in government, business, and natural and social sciences.
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Mathematical foundations of modern Business statistics were laid in the 17th century with the development of the probability theory by Gerolamo Cardano, Blaise Pascal and Pierre de Fermat.
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Business statistics originated the concepts of sufficiency, ancillary statistics, Fisher's linear discriminator and Fisher information.
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Descriptive Business statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population.
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Misuse of Business statistics can produce subtle but serious errors in description and interpretation—subtle in the sense that even experienced professionals make such errors, and serious in the sense that they can lead to devastating decision errors.
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Misuse of Business statistics can be both inadvertent and intentional, and the book How to Lie with Statistics, by Darrell Huff, outlines a range of considerations.
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Mathematical Business statistics includes not only the manipulation of probability distributions necessary for deriving results related to methods of estimation and inference, but various aspects of computational Business statistics and the design of experiments.
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Business statistics applies statistical methods in econometrics, auditing and production and operations, including services improvement and marketing research.
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Typical Business statistics course covers descriptive Business statistics, probability, binomial and normal distributions, test of hypotheses and confidence intervals, linear regression, and correlation.
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Traditionally, Business statistics was concerned with drawing inferences using a semi-standardized methodology that was "required learning" in most sciences.
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