Probability & Statistics with R for Engineers and Scientists (Classic Version)
Published on 18. September 2020
Book
Paperback/Softback
528 pages
978-0-13-499535-9 (ISBN)
Description
This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles.
This text grew out of the author's notes for a course that he has taught for many years to a diverse group of undergraduates. The early introduction to the major concepts engages students immediately, which helps them see the big picture, and sets an appropriate tone for the course. In subsequent chapters, these topics are revisited, developed, and formalized, but the early introduction helps students build a true understanding of the concepts. The text utilizes the statistical software R, which is both widely used and freely available (thanks to the Free Software Foundation). However, in contrast with other books for the intended audience, this book by Akritas emphasizes not only the interpretation of software output, but also the generation of this output. Applications are diverse and relevant, and come from a variety of fields.
This text grew out of the author's notes for a course that he has taught for many years to a diverse group of undergraduates. The early introduction to the major concepts engages students immediately, which helps them see the big picture, and sets an appropriate tone for the course. In subsequent chapters, these topics are revisited, developed, and formalized, but the early introduction helps students build a true understanding of the concepts. The text utilizes the statistical software R, which is both widely used and freely available (thanks to the Free Software Foundation). However, in contrast with other books for the intended audience, this book by Akritas emphasizes not only the interpretation of software output, but also the generation of this output. Applications are diverse and relevant, and come from a variety of fields.
More details
Series
Language
English
Place of publication
Boston
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 251 mm
Width: 203 mm
Thickness: 23 mm
Weight
862 gr
ISBN-13
978-0-13-499535-9 (9780134995359)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Michael G. Akritas has been teaching Statistics at Penn State University since 1985. He is the author of approximately 100 research publications dealing with a wide range of statistical topics. He has supervised 18 Ph.D. and 12 M.Sc. students and is currently supervising three Ph.D. students. He is co-Founder of the International Society for Nonparametric Statistics, former Director of the National Statistical Consulting Center for Astronomy and co-Editor of the Journal of Nonparametric Statistics. He held a three year affiliation with the National Technical University of Athens, and visiting appointments at MIT, Texas A&M University, University of Pennsylvania, University of Goettingen, University of Cyprus, Australian National University, and UNICAMP. He has been an elected Fellow of the Institute of Mathematical Statistics and of the American Statistical Association since 2001.
Content
1. Basic Statistical Concepts
1.1 Why Statistics?
1.2 Populations and Samples
1.2.1 Exercises
1.3 Some Sampling Concepts
1.3.1 Representative Samples
1.3.2 Simple Random Sampling, and Stratied Sampling
1.3.3 Sampling With and Without Replacement
1.3.4 Non-representative Sampling
1.3.5 Exercises
1.4 Random Variables and Statistical Populations
1.4.1 Exercises
1.5 Basic Graphics for Data Visualization
1.5.1 Histograms and Stem and Leaf Plots
1.5.2 Scatterplots
1.5.3 Pie Charts and Bar Graphs
1.5.4 Exercises
1.6 Proportions, Averages and Variances
1.6.1 Population Proportion and Sample Proportion
1.6.2 Population Average and Sample Average
1.6.3 Population Variance and Sample Variance
1.6.4 Exercises
1.7 Medians, Percentiles and Box Plots
1.7.1 Exercises
1.8 Comparative Studies
1.8.1 Basic Concepts and Comparative Graphics
1.8.2 Lurking Variables and Simpson's Paradox
1.8.3 Causation: Experiments and Observational Studies
1.8.4 Factorial Experiments: Main E
1.1 Why Statistics?
1.2 Populations and Samples
1.2.1 Exercises
1.3 Some Sampling Concepts
1.3.1 Representative Samples
1.3.2 Simple Random Sampling, and Stratied Sampling
1.3.3 Sampling With and Without Replacement
1.3.4 Non-representative Sampling
1.3.5 Exercises
1.4 Random Variables and Statistical Populations
1.4.1 Exercises
1.5 Basic Graphics for Data Visualization
1.5.1 Histograms and Stem and Leaf Plots
1.5.2 Scatterplots
1.5.3 Pie Charts and Bar Graphs
1.5.4 Exercises
1.6 Proportions, Averages and Variances
1.6.1 Population Proportion and Sample Proportion
1.6.2 Population Average and Sample Average
1.6.3 Population Variance and Sample Variance
1.6.4 Exercises
1.7 Medians, Percentiles and Box Plots
1.7.1 Exercises
1.8 Comparative Studies
1.8.1 Basic Concepts and Comparative Graphics
1.8.2 Lurking Variables and Simpson's Paradox
1.8.3 Causation: Experiments and Observational Studies
1.8.4 Factorial Experiments: Main E