Description
For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding. MyStatLab is not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. 1. Introduction to Statistics and Data Analysis 1.1 Overview: Statistical Inference, Samples, Populations, and the Role of Probability 1.2 Sampling Procedures; Collection of Data 1.3 Measures of Location: The Sample Mean and Median Exercises 1.4 Measures of Variability Exercises 1.5 Discrete and Continuous Data 1.6 Statistical Modeling, Scientific Inspection, and Graphical Methods 1.7 General Types of Statistical Studies: Designed Experiment, Observational Study, and Retrospective Study Exercises 2. Probability 2.1 Sample Space 2.2 Events Exercises 2.3 Counting Sample Points Exercises 2.4 Probability of an Event 2.5 Additive Rules Exercises 2.6 Conditional Probability, Independence and Product Rules Exercises 2.7 Bayes Rule Exercises Review Exercises 2.8 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters 3. Random Variables and Probability Distributions 3.1 Concept of a Random Variable 3.2 Discrete Probability Distributions 3.3 Continuous Probability Distributions Exercises 3.4 Joint Probability Distributions Exercises Review Exercises 3.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters 4. Mathematical Expectation 4.1 Mean of a Random Variable Exercises 4.2 Variance and Covariance of Random Variables Exercises 4.3 Means and Variances of Linear Combinations of Random Variables 4.4 Chebyshevs Theorem Exercises Review Exercises 4.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters 5. Some Discrete Probability Distributions 5.1 Introduction and Motivation 5.2 Binomial and Multinomial Distributions Exercises 5.3 Hypergeometric Distribution Exercises 5.4 Negative Binomial and Geometric Distributions 5.5 Poisson Distribution and the Poisson Process Exercises Review Exercises 5.6 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters 6. Some Continuous Probability Distributions 6.1 Continuous Uniform Distribution 6.2 Normal Distribution 6.3 Areas under the Normal Curve 6.4 Applications of the Normal Distribution Exercises 6.5 Normal Approximation to the Binomial Exercises 6.6 Gamma and Exponential Distributions 6.7 Chi-Squared Distribution 6.8 Beta Distribution 6.9 Lognormal Distribution (Optional) 6.10 Weibull Distribution (Optional) Exercises Review Exercises 6.11 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters 7. Functions of Random Variables (Optional) 7.1 Introduction 7.2 Transformations of Variables 7.3 Moments and Moment-Generating Functions Exercises 8. Sampling Distributions and More Graphical Tools 8.1 Random Sampling and Sampling Distributions 8.2 Some Important Statistics Exercises 8.3 Sampling Distributions 8.4 Sampling Distribution of Means and the Central Limit Theorem Exercises 8.5 Sampling Distribution of S2 8.6 t-Distribution 8.8 Quantile and Probability Plots Exercises Review Exercises 8.9 Potential Misconceptions and Hazards; Relationship to Mate
