Probability and Statistics for Engineers and Scientists (7th Edition)

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.

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.