1979Clinical Pharmacology & TherapeuticsRequires access

XLIX. The basic data structures used in quantitative indexes

Alvan R. Feinstein

Open publisher page 1 citations

Abstract

The domain of statistics is divided into two parts: descriptive and inferential. The inferential part contains the mathematical strategies that produce P values, confidence intervals, and other features of stochastic probability. The descriptive part is more mundane and often receives only cursory attention. In most textbooks and in classroom instruction, the descriptive features of statistics are usually taught rapidly as a necessary but relatively unimportant background for the inferential work. The means, proportions, rates, variances, distributions, correlation coefficients, and other descriptive statistical entities are generally presented as mere participants in the “important” inferential decisions that come later.

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What this paper is about

The domain of statistics is divided into two parts: descriptive and inferential. The inferential part contains the mathematical strategies that produce P values, confidence intervals, and other features of stochastic probability. The descriptive part is more mundane and often receives only cursory attention. In most textbooks and in classroom instruction, the descriptive features of statistics are usually taught rapidly as a necessary but relatively unimportant background for the inferential work. The means, proportions, rates, variances, distributions, correlation coefficients, and other descriptive statistical entities are generally presented as mere participants in the “important” inferential decisions that come later.

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Available abstract

The domain of statistics is divided into two parts: descriptive and inferential. The inferential part contains the mathematical strategies that produce P values, confidence intervals, and other features of stochastic probability. The descriptive part is more mundane and often receives only cursory attention. In most textbooks and in classroom instruction, the descriptive features of statistics are usually taught rapidly as a necessary but relatively unimportant background for the inferential work. The means, proportions, rates, variances, distributions, correlation coefficients, and other descriptive statistical entities are generally presented as mere participants in the “important” inferential decisions that come later.

Key concepts: Descriptive statistics, Statistical inference, Statistics, Mathematical statistics, Statistical analysis, Probability and statistics, Psychology, Mathematics

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