Bibliogr.: p. 235.

ch. 1. Introduction --
ch. 2. Classes of models and statistical inference --
ch. 3. Sampling and descriptive statistics --
ch. 4. Survey of basic probability --
ch. 5. Introduction to statistical estimation --
ch. 6. Testing hypotheses --
ch. 7. Basic regression and analysis of variance.

"Designed for a first course in statistics for graduate or upper-level undergraduate students, Basic Statistical Methods and Models builds a practical foundation in the use of statistical tools and imparts a clear understanding of their underlying assumptions and limitations. Without getting bogged down in proofs and derivations, thorough discussions help readers understand why the stated methods and results are reasonable. The use of the statistical software Minitab is integrated throughout the book, giving readers valuable experience with computer simulations and problem-solving techniques. The author focuses on applications and the models appropriate to each problem while emphasizing Monte Carlo methods, the Central Limit Theorem, confidence intervals, and power functions." "The text assumes some degree of maturity in mathematics, but it does not require the use of calculus. This, along with its very clear explanations, generous number of exercises, and demonstrations of the extensive uses of statistics in diverse areas of application make Basic Statistical Methods and Models highly accessible to readers in a wide range of disciplines."--Jacket.