Description
Illustrates the use of probabilistic models and statistical methodology for applications in science and engineering. Emphasizing methodology, while not entirely neglecting theory, chapters introduce students to random variables and probability distributions, discrete and continuous probability distributions, functions of random variables, sampling distributions and data descriptions, one- and two-sample estimation problems, simple linear regression and correlation, multiple linear regression, certain nonlinear regression models, multiple factorial experiments, nonparametric statistics, and statistical quality control. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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This classic book provides a rigorous introduction to basic probability theory and statistical inference that is motivated by interesting, relevant applications. It assumes readers have a background in calculus, and offers a unique balance of theory and methodology. Chapter topics cover an introduction to statistics and data analysis, probability, random variables and probability distributions, mathematical expectation, some discrete probability distributions, some continuous probability distributions, functions of random variables, fundamental sampling distributions and data descriptions, one- and two-sample estimation problems, one- and two-sample tests of hypotheses, simple linear regression and correlation, multiple linear regression and certain nonlinear regression models, one factor experiments: general, factorial experiments (two or more factors), 2k factorial experiments and fractions, nonparametric statistics, and statistical quality control. For individuals trying to apply statistical concepts to real-life, and analyze and interpret data.
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