This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance of 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.
This latest edition is also available in as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book.
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 ...
"For these special editions, the editorial team at Pearson has collaborated with educators across the world to address a wide range of subjects and requirements, equipping students with the best possible learning tools.
This latest edition is also available in as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book.
Suitable for a one or two semester course, this title takes a practical approach to methods of statistical modelling and data analysis that are most often used in scientific work.
Reviews fundamental concepts and applications of probability and statistics. After a general overview, it considers special types of random variables, using examples which illustrate their wide variety of applications. Also...
Students using this text should have the equivalent of the completion of one semester of differential and integral calculus.
For junior/senior undergraduates taking probability and statistics as it applied to engineering, science or computer science. With its unique balance of theory and methodology, this classic text provides a rigorous...
The book also features: Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and ...
Probability and Statistics for Engineering and the Sciences + Enhanced Webassign Access