A MODERN INTRODUCTION TO PROBABILITY AND STATISTICS: UNDERSTANDING WHY AND HOW (SPRINGER TEXTS IN STATISTICS)

"This textbook provides a well-written first course in probability and statistics...It is a book that has been written based on the long teaching experience of the authors and I would certainly recommend it for university coursework." Short Book Reviews of the International Statistical Institute, December 2005 TOC:Why Probability and Statistics?- Outcomes, Events and Probability.- Conditional Probability and Independence.- Discrete Random Variables.- Continuous Random Variables.- Simulation.- Expectation and Variance.- Computations with Random Variables.- Joint Distributions and Independence.- Covariance and Correlation.- More Computations with More Random Variables.- The Poisson Process.- The Law of Large Numbers.- The Central Limit Theorem.- Exploratory Data Analysis: Graphical Summaries.- Exploratory Data Analysis: Numerical Summaries.- Basic Statistical Models.- The Bootstrap.- Unbiased Estimators.- Efficiency and Mean Squared Error.- Maximum Likelihood.- The Method of Least Squares.- Confidence Intervals for the Mean.- More on Confidence Intervals.- Testing Hypotheses: Essentials.- Testing Hypotheses: Elaboration.- The t-test.- Comparing Two Samples.- Datasets.- Appendix A: Answers to Selected Exercises.- Appendix B: Solutions to Selected Exercises.- References.- Index.

Idioma: INGLÉS