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This applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variability. Designed for students with a background in calculus, it reinforces basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.
- Sales Rank: #869569 in Books
- Published on: 2005-01-30
- Original language: English
- Number of items: 1
- Dimensions: 9.22" h x 1.19" w x 8.20" l,
- Binding: Hardcover
- 752 pages
Review
"Generally, I think the pedagogy is excellent, providing an almost holistic introduction to statistics, both its mathematical and applications sides. Elements of the subject are introduced in increasing layers of complexity, at a rate that is challenging yet measured. Masterfully done. My overall impression of the book is quite favorable and actually I am considering this text for my next cycle of classes. Strengths: excellent use of examples to illustrate concepts; strong exercise selections; the discussions are generally clear, animated, and focused with the main drive of the text in mind. All the necessary topics central to modern statistics are introduced. The level of the text is quite good for an undergraduate introductory course. Many rather difficult ideas are presented simply, but effectively enough to prepare students for later topics and courses. And the text really bares the soul of statistics. The text motivates the theory by keeping it connected to real-world applications." — David F. Snyder, Texas State University
"Probability and Statistical Inference is a great text to use for a one-year course, where the students are just becoming mathematically prepared. The authors write with great care and clearly develop and motivate the subject. This edition also contains a chapter on Bayesian methods. Chapter 7 is an interesting and modern treatment of the subject—a subject that has included some controversy. Although I am a probabilist, I am certainly pleased to see this treatment in an undergraduate text. Bayesian methods have long needed suitable treatment at the undergraduate level. It provides an up-to-date and complete treatment of mathematics of probability and statistics. This edition also includes many new examples, applications, and exercises. Each of these has improved in an already outstanding text." — Randall Swift, California State Polytechnic University, Pomona
"This latest version of Hogg and Tanis contains many more realistic data scenarios that rely much less on coin tossing and dice and card examples. Students will likely better understand the material if they can relate to the examples. The authors strike a good balance between readability and rigor. The material is accurately presented and theorems are accurate. I am glad to see section 6.13 'Resampling Methods' induded. The 'bootstrap' has been around now for 20 years but many mathematical statistics books still neglect it or relegate it to the exercises. This is a good indication that the text is up-to-date." — Paul Joyce, University of Idaho
"This is a good, solid, calculus-based introduction to probability and statistics at the sophomore-junior level. I have used this textbook twice for such a course, and would like to use it again in the future." — Ching-Yuan Chiang, James Madison University
"The examples in the book are very clear and easy to follow. My students would benefit from this book more than our current textbook." — Mark Ghamsary, Loma Linda University
From the Publisher
An accessible introduction to the mathematics of probability and statistics for students with a background in calculus. Numerous applications help explain and motivate the concepts.
From the Inside Flap
Preface
We are pleased with the reception that was given to the first five editions of Probability and Statistical Inference. The sixth edition is still designed for use in a course having from three to six semester hours of credit. No previous study of statistics is assumed, and a standard course in calculus provides an adequate mathematical background. Certain sections have been starred and are not needed in subsequent sections. This, however, does not mean that these starred sections are unimportant, and we hope many of you will study them.
We still view this book as the basis of a junior or senior level course in the mathematics of probability and statistics that is taught by many departments of mathematics and/or statistics. We have tried to make it more "user friendly"; yet we do want to reinforce certain basic concepts of mathematics, particularly calculus. To help the student with methods of algebra of sets and calculus, we include a Review of Selected Mathematical Techniques in Appendix A. This review includes a method that makes integration by parts easier. Also we derive the important Rule of 72 that provides an approximation to the number of years necessary for money to double. MAJOR CHANGES IN THIS EDITION
Chapter 1 still provides an excellent introduction to good descriptive statistics and exploratory data analysis and the corresponding empirical distributions. However, probability models are also introduced in Chapter 1 so that the student recognizes from the beginning that the characteristics of the empirical distributions are estimates of those of probability distributions. Hopefully, this creates some interest among students in checking to see if a probability model is appropriate for the situation under consideration throughout the text.
Chapters 2-4 provide concepts in probability and basic distributions. These have been simplified somewhat from the previous edition by introducing a few of the easiest distributions through examples. Also the probability generating function has been dropped in this edition, although we note that the moment-generating function can serve in that capacity. Of course, the latter can also be used to compute the moments of a distribution.
By request of many statisticians, we have introduced multivariate distributions much earlier, but in such a way that only the first section of that chapter is needed for the chapters that follow on techniques used in statistical inference. Hence, if an instructor so desires, he or she can start statistical methods sooner without conditional distributions.
While this book is written primarily as a mathematical introduction to probability and statistics, there are a great many examples and exercises concerned with applications. For illustrations, the reader will find applications in the areas of biology, education, economics, engineering, environmental studies, exercise science, health science, manufacturing, opinion polls, psychology, sociology, and sports. That is, there are many exercises in the text, some illustrating the mathematics of probability and statistics but a great number are concerned with applications. We are certainly more concerned with model checking in this edition than in the previous editions.
In addition, there is major effort to emphasize confidence intervals more than previously, and we clearly spell out the relationship between confidence intervals and tests of hypotheses. In that regard, we have increased the emphasis on one-sided confidence intervals somewhat because often a practitioner wants a lower or upper bound for the parameter in question, and these have a natural relationship with one-sided tests of hypotheses.
The chapter on confidence intervals is so organized that the instructor can introduce early basic concepts of regression and distribution-free techniques, if he or she chooses to do so. That is, the separate chapter on nonparametric methods has been dropped, and those basic concepts are included among the other methods of statistical inference. After the considerations of the first few basic sections in the chapters on estimation and tests, the instructor may select among some of the later sections in each of those chapters. It is also noted that, at the suggestion of two of the reviewers, Section 8.11 on resampling methods is new to this edition, and we hope some instructors will choose to consider this new technique of statistical inference.
While the text is written primarily for a two-semester sequence of a probability course (selections from Chapters 1-6) followed by a statistical inference course (selections from Chapters 7-10), it can be used for a 4-credit hour semester course for those students with a good calculus background. In such a course, Chapters 1-4 (except the starred sections) are considered followed by Section 5.1 and most of Chapter 6; these make up about 70 percent of the course. The remaining 30 percent consists of selections from Chapters 7 and 8, unless the instructor wants to consider some of the theory given in the early part of Chapter 9. Those interested in the statistical methods used in quality improvement would want to consider at least part of Chapter 10.
Different from most textbooks, we have included a prologue, a centerpiece, and an epilogue. The main emphasis in these is that variation occurs in almost every process, and the study of probability and statistics helps us understand this variability. Accordingly, the study of statistics is extremely useful in many fields of endeavor and can lead students to interesting positions in the future. FEATURES
Throughout the book, figures and real applications will help the student understand statistics and what statistical methods can accomplish. For some exercises, it is assumed that calculators or computers are available; thus the solutions will not always involve "nice" numbers. Solutions using a computer are given if a complicated data set is involved. The data sets for all of the exercises are available on a data disk and on the Web. ANCILLARIES
A Solutions Manual containing worked-out solutions to the even-numbered exercises in the text is available to instructors from the publisher. Many of the numerical exercises were solved using Maple. For additional exercises that involve simulations, a separate manual Probability & Statistics: Explorations with MAPLE, second edition, by Zaven Karian and Elliot Tanis is available for purchase. Several exercises in that manual also make use of the power of Maple as a computer algebra system.
A CD-ROM is new for this edition. There are two folders on the CD. The folder titled "Data" includes the data files for most of the exercises and examples in the text. Each chapter for which data files are given has it's own folder and most include separate folders for pertinent sections. The files are saved in a number of different formats to provide maximum flexibility to the user. The folder labeled figures contains two types of figures. Several of the figures in the text are stored as Minitab projects (.mpj) within chapter folders. They can be opened from Minitab or it may be possible to double click on one of these files and Minitab will open the selected file. The other figures included in this folder were generated using Maple. These include animated versions of several figures in the text that allow the user to view the figures in a dynamic environment that will help clarify and reinforce the concepts being presented. To view the animated figures, as well as others that were generated using Maple, the user must have access to a web browser such as Microsoft Explorer or Netscape Navigator. If you have a web browser, the most efficient approach to viewing the figures is to open the Figures Folder and double click on the directory.htm file. This file should open in your web browser and present you with a list of figures from which to select.
A web page for this text is available at prenhall/hogg. Check out this web page to see what is available.
Most helpful customer reviews
60 of 64 people found the following review helpful.
Not as Good as the 6th Edition!
By Patrick Goetz
I am currently teaching statistics (using a different textbook) and have been using the 6th edition of Hogg/Tanis as a reference. In my opinion, this is a pretty good text for someone who A) already has some idea of what statistics is all about and B) has a thorough understanding of calculus, which Hogg/Tanis make liberal use of. For someone who likes and understands calculus,
this is a much better introductory text than those that studiously avoid any mention of higher level mathematics. I give the 6th edition a 5-star rating based on the sections I've looked at so far.
With that said, I'm sorry to report that the 7th edition is not as good as the 6th. The authors have re-organized the material "for better logical organization", but in the process have lost some pedagogical clarity. For example, the relatively important student's t distribution has been relegated to an obscure example buried in a new chapter on the normal distribution, and the formerly excellent explanation of how this is derived is gone.
And speaking of "The Normal Distribution" chapter, do I really want all things normal relegated to a separate chapter? The pervasive use and importance of this distribution in statistics makes me think that it might be better to let the normal distribution pop up whenever it needs to be invoked, as was the case in the 6th edition. Including a "Sampling Distribution Theory" chapter (as was done in the 6th edition) makes a lot more sense than what they've done now. The new chapter on Bayesian Methods is short, and not terribly useful. Relegating this material to section 9.5 in a chapter on "Theory of Statistical Inference", as was done in the 6th edition was a much better decision.
The section on "Exploratory Data Analysis" (histograms and stemplots) has been moved from an introductory chapter (which no longer exists) to the chapter on "Continuous-Type Data". How does this make any sense? And yes, it is most definately a good idea to have an introductory chapter which talks about basic concepts and data visualizations. In the 7th edition, the mean, median, and standard deviation are first mentioned in chapter 2.
Finally, why on earth do authors think that randomly adding color to a textbook and widening the pages to allow for giant margins on every page makes a text more readable/useful when in fact just the opposite is the case? The wide margins add nothing and make the book both heavier and more unwieldy, and the blue section headings and graphs give it the feel of a junior high school algebra text. The compact elegance of the 6th edition stands in stark contrast to the large and comparatively garish 7th edition.
This revision has all the feel of something that was driven strictly by textbook marketing concerns and has nothing to do with either pedagogy or an interest in producing a excellent statistics book.
My advice? If you're looking for something for self-study or reference, get the 6th edition instead. It's better, and you can get a used copy on Amazon for next to nothing, since the lemmings have all switched to using the 7th edition and there are a lot of unwanted copies of the 6th floating around.
The nonsense of constantly producing new (and often inferior) editions of textbooks just so that publishers can make more money needs to be nipped in the bud.
8 of 8 people found the following review helpful.
a (yawn) mechanical approach to mathematics
By A Customer
I studied the first 8 chapters of this book instead of attending the undergraduate lecture. This was a mistake. Tanis & Hoggs present probability and statistics, an otherwise interesting topic, in the most mechanical way imaginable. There is no reference (that I can recall) to any underlying mathematical ideas or questions, nor to the problems which originially prompted Poisson, Bernoulli, Gauss, etc. to inquire about the nature of "randomness" in physical events. The authors seem to suppose that their examples demonstrate such things by proxy. This book may make a decent reference for advanced students, but should not be used to teach those seeing prob & stat for the first time... that is, unless, you want it to also be their last.
9 of 10 people found the following review helpful.
Illogic organization and non-intuitive explanation
By A Customer
i'm not sure whether it's useful as a reference, but it's far from being a good textbook. obviously the authors didn't care to explain anything clearly. all they wanted was to write down all the relevant formulas to finish their book. no intuition is given at all. it's a pain to read and i would recommend both instructors and students NOT to use this book.
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