Probability models, statistical methods, and the information to be gained from them is vital for work in business, engineering, sciences (including social and behavioral), and other fields. Data must be properly collected, analyzed and interpreted in order for the results to be used with confidence.Award-winning author George Roussas introduces readers with no prior knowledge in probability or statistics to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability and Statistical Inference provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. Contains more than 200 illustrative examples discussed in detail, plus scores of numerical examples and applications to illustrate points and concepts.First eight chapters can be used independently for an introductory course in probabilityProvides a substantial number of proofs INDICE: Chapter 1 Some Motivating Examples and Some Fundamental Concepts Chapter 2 The Concept of Probability and Some Basic Results Chapter 3 Numerical Characteristics of a Random Variable, Some Special Random Variables Chapter 4 Joint and Conditional p.d.f.'s, Conditional Expectation and Variance, Moment Generating Function, Covariance and Correlation Coefficient Chapter 5 Independence of Random Variables and Some Applications Chapter 6 Transformation of Random Variables Chapter 7 Some Modes of Convergence of Random Variables, Applications Chapter 8 An Overview of Statistical Inference Chapter 9 Point Estimation Chapter 10 Confidence Intervals and Confidence Regions Chapter 11 Testing Hypotheses Chapter 12 More About Testing Hypotheses Chapter 13 A Simple Linear Regression Model Chapter 14 Two Analysis of Variance Models Chapter 15 Some Topics in Nonparametric Inference
- ISBN: 978-0-12-800114-1
- Editorial: Academic Press
- Encuadernacion: Cartoné
- Páginas: 528
- Fecha Publicación: 01/10/2014
- Nº Volúmenes: 1
- Idioma: Inglés