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Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers d… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code needed.
Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedures commonly used by practicing engineers and scientists. Utilizing real data from actual studies across life science, engineering, computing and business, this useful introduction supports reader comprehension through a wide variety of exercises and examples. End-of-chapter reviews of materials highlight key ideas, also discussing the risks associated with the practical application of each material. In the new edition, coverage includes information on Big Data and the use of R.
This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.
Undergraduate and graduate students in statistics, engineering or other sciences
CHAPTER 1
Introduction to statisticsCHAPTER 2 Descriptive statistics
CHAPTER 3
Elements of probabilityCHAPTER 4
Random variables and expectationCHAPTER 5
Special random variablesCHAPTER 6
Distributions of sampling statisticsCHAPTER 7
Parameter estimationCHAPTER 8 Hypothesis testing
CHAPTER 9
RegressionCHAPTER 10
Analysis of varianceCHAPTER 11
Goodness of fit tests and categorical data analysisCHAPTER 12 Nonparametric hypothesis tests
CHAPTER 13 Quality control
CHAPTER 14 Life testing
CHAPTER 15 Simulation, bootstrap statistical methods, and permutation tests
CHAPTER 16 Machine learning and big data
SR