Buch, Englisch, 824 Seiten, Format (B × H): 201 mm x 236 mm, Gewicht: 1338 g
Buch, Englisch, 824 Seiten, Format (B × H): 201 mm x 236 mm, Gewicht: 1338 g
ISBN: 978-0-12-088494-0
Verlag: Elsevier Science
Advanced Statistics from an Elementary Point of View is a highly readable text that communicates the content of a course in mathematical statistics without imposing too much rigor. It clearly emphasizes the connection between statistics and probability, and helps students concentrate on statistical strategies without being overwhelmed by calculations.
The book provides comprehensive coverage of descriptive statistics; detailed treatment of univariate and bivariate probability distributions; and thorough coverage of probability theory with numerous event classifications.
This book is designed for statistics majors who are already familiar with introductory calculus and statistics, and can be used in either a one- or two-semester course. It can also serve as a statistics tutorial or review for working professionals.
Students who use this book will be well on their way to thinking like a statistician in terms of problem solving and decision-making. Graduates who pursue careers in statistics will continue to find this book useful, due to numerous statistical test procedures (both parametric and non-parametric) and detailed examples.
Zielgruppe
Advanced undergraduate or beginning graduate students majoring in mathematics, statistics, engineering, actuarial science, economics/finance and life sciences. It can be used for either a one semester course or two semester course sequence. The book will also interest professionals seeking exposure to data analysis. The reader requires some grounding in calculus
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1 Introduction
2 Elementary Descriptive Statistical Techniques
4 Random Variables and Probability Distributions
5 Bivariate Probability Distributions
6 Discrete Parametric Probability Distributions
7 Continuous Parametric Probability Distributions
8 Sampling and the Sampling Distribution of a Statistic
9 The Chi-Square, Student's t, and Snedecor's F Distributions
10 Point Estimation and Properties of Point Estimators
11 Interval Estimation and Confidence Interval Estimates
12 Tests of Parametric Statistical Hypotheses
13 Nonparametric Statistical Techniques
14 Testing Goodness of Fit
15 Testing Goodness of Fit: Contingency Tables
16 Bivariate Linear Regression and Correlation
Appendix A
Successive Difference to the Variance
Solutions to Selected Exercises
References and Suggested Reading
Index
