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Applied Statistics for Engineers and Physical Scientists (3rd Edition), by Johannes Ledolter, Robert V. Hogg
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This hugely anticipated revision has held true to its core strengths, while bringing the book fully up to date with modern engineering statistics. Written by two leading statisticians, Statistics for Engineers and Physical Scientists, Third Edition, provides the necessary bridge between basic statistical theory and interesting applications. Students solve the same problems that engineers and scientists face, and have the opportunity to analyze real data sets. Larger-scale projects are a unique feature of this book, which let students analyze and interpret real data, while also encouraging them to conduct their own studies and compare approaches and results.
This book assumes a calculus background. It is appropriate for undergraduate and graduate engineering or physical science courses or for students taking an introductory course applied statistics.
- Sales Rank: #1017317 in Books
- Published on: 2009-01-07
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.30" w x 7.00" l, 2.15 pounds
- Binding: Paperback
- 608 pages
From the Publisher
Written by two of the leading figures in statistics, this highly regarded volume thoroughly addresses the full range of required topics.
From the Back Cover
This hugely anticipated revision has held true to its core strengths, while bringing the book fully up to date with modern engineering statistics. Written by two leading statisticians,Statistics for Engineers and Physical Scientists,3/e,provides the necessary bridge between basic statistical theory and interesting applications. Readers solve the same problems that engineers and scientists face, and have the opportunity to analyze real data sets. Larger-scale projects are a unique feature of this book, which let readers analyze and interpret real data, while also encouraging them to conduct their own studies and compare approaches and results. This book assumes a calculus background. Collection and Analysis of Information; Probability Models and Discrete Distributions; Continuous Probability Models; Statistical Inference: Sampling Distribution, Confidence Intervals, and Tests of Hypotheses; Statistical Process Control; Experiments with One Factor; Experiments with Two or More Factors; Regression Analysis. For all readers interested in applied statistics.
About the Author
Johannes Ledolter is a Professor of Statistics and Actuarial Sciences at the University of Iowa as well as a C. Maxwell Stanley Professor of International Operations Management at the Henry B. Tippie College of Business. Ledolter received his M.S. and Ph.D. degrees in Statistics from the University of Wisconsin-Madison along with an M.S degree in Social and Economic Statistics from the University of Vienna. His research interests are in time series analysis, forecasting, and applied statistical modeling. His publications have appeared in Biometrika, Technometrics, Communications in Statistics, and Management Science. He is the co-author of several books including Experimental Design with Applications in Marketing and Service Operations, Introduction to Regression Modeling, Statistical Quality Control, and Statistical Methods for Forecasting.
Robert V. Hogg, Professor Emeritus of Statistics at the University of Iowa since 2001, received his B.A. in mathematics at the University of Illinois and his M.S. and Ph.D. degrees in mathematics, specializing in actuarial sciences and statistics, from the University of Iowa. Known for his gift of humor and his passion for teaching, Hogg has had far-reaching influence in the field of statistics. Throughout his career, Hogg has played a major role in defining statistics as a unique academic field, and he almost literally "wrote the book" on the subject. He has written more than 70 research articles and co-authored four books including Introduction of Mathematical Statistics, 6th edition, with J. W. McKean and A.T. Craig, as well as Probability and Statistical Inference, 8th edition and A Brief Course in Mathematical 1st edition, both with E.A. Tanis. His texts have become classroom standards used by hundreds of thousands of students
Among the many awards he has received for distinction in teaching, Hogg has been honored at the national level (the Mathematical Association of America Award for Distinguished Teaching), the state level (the Governor's Science Medal for Teaching), and the university level (Collegiate Teaching Award). His important contributions to statistical research have been acknowledged by his election to fellowship standing in the ASA and the Institute of Mathematical Statistics.
Most helpful customer reviews
16 of 17 people found the following review helpful.
This book is pretty bad...
By Joshua P. Jung
Alright, a little background. I am an engineering student at UIC and am currently in the field of software engineering and have been for 5+ years. I've decided to go back to school to get the degree saying I know what I already know.
I consider myself fairly intelligent and got straight A's in Calculus 1,2,3 and Differential Equations so I was always good at math.
This book could not be more confusing:
1) Explanations and proofs are half-assed. Phrases like "It is easy to show..." are often insufficent. Like another review said, there is almost an underlying assumption that you already know the material the book is explaining.
2) Notation is often left unexplained or an explanation is half-hazardously thrown in as an after-thought. Forget ever being able to go back and sift through all the text to try and find those 10 words explaining the notation again as they are often hidden in a massive paragraph. I feel like every paragraph is written by a mildly presumptuous and assuming person. It's as if the entire attitude is a passive "you probably already know this so I won't explain it that well so we can move on..."
3) The book feels like it was written by an English major describing the story of statistics. I am constantly trying to find structure in the massive paragraph after paragraph. I'm trying to picture things mathematically and it never ceases to amaze me just how bad the explanations are.
3) Key equations are never highlighted in the book. Can't you put a freaking box around it and say "Important!" or "Standard Deviation"? No, instead you have to read reams of paragraphs interspersed with half-explained proofs and things like "it is easy to show" and then several paragraphs later "and therefore we conclude" and then, in the same font, the most important piece of information is given.
4) Organization of chapters is completely uninspired. Chapters are odd mixtures of proofs, explanations, stories, and examples. Sometimes important things are bolded and sometimes not. Sometimes definitions are given in neat little boxes and sometimes they are not. Often important equations or explanations are given in examples - rather than before. Sometimes proofs are half-assed. Sometimes examples do not prepare you for the homework problems.
Ultimately I have had to resort to watching tons of YouTube clips and reading other articles online to supplement this book because it has been so useless to me. Every explanation is hard to follow whereas a YouTube video clip will often resolve the entire thing for me in 2-3 minutes.
The Final Kicker...
This is what really sealed my hatred of this book for me. Problem 2.2-16 is about Pap smears and how unreliable they are. The irony? The source of this data is not given. For all I know they just made this up. But girls in class were asking if they should stop taking pap smears. Of course, we have no idea if the data given in that homework problem was any good. We don't know where it came from.
You have got to be kidding. The statisticians who wrote this book are providing doubts about a medical test by throwing out numbers and then not clarifying that it is hypothetical or where they got their data. How professional and what wonderful handling of data.
If you can help it, avoid this book. Go watch some YouTube clips and you'll be far smarter far faster.
8 of 9 people found the following review helpful.
Not clear at all
By A Customer
This book was used as a text for an intro statistics class, and proved to be completely useless. First of all it fails to explain any of the information in terms understandable by the reader, and thus is useless to anyone who doesn't already know the material. Second, the examples it does provide (few as they are) show the simplest cases possible, that do not apply the information covered in that section. The examples, if a solution is provided (oftentimes they say in one sentence that the solution should be obvious to anyone, and don't provide a solution) skip steps and are generally confusing. In summary, this book should only be used if you already understand everything in it and I would thereby rate it as a pass, unless of course you are looking for a handbook or reference.
2 of 2 people found the following review helpful.
horrible
By frank
I hate that I am subjected to this book. It has hardly any examples and then expects you to know how to do homework problems that are way harder and completely different from the examples. UIC is truly foolish for using this book and it clearly shows how bought they are by the textbook oligopoly. Garbage
See all 16 customer reviews...
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