Book Description
Intended for use as a core text or to supplement any introductory or intermediate level statistics course, this book presents the basics of the SAS system in a well-paced, structured, non-threatening manner. It provides an introduction to the SAS system for data management, analysis, and reporting using the subset of the language ideally suited for beginning students, while at the same time serving as a useful reference for intermediate or advanced users. Students learn the language's power and flexibility with many real-world examples drawn from the author's industry experience. Beginning with an overview of the system, this text shows students how to read data, perform simple analyses, and produce simple reports. More complex topics are carefully introduced, guiding students to manage multiple datasets and write custom reports. More advanced statistical techniques such as correlation, regression, and analysis of variance are presented in later chapters.
Customer Reviews:
Excellent beginner's book.......2004-01-09
I used this book in grad school to refresh my very limited SAS knowledge for a course I was doing. I'd used other books during my undergrad days, but none of them was as helpful as this one. It's a good way for a beginner to ease themselves into SAS without getting tangled in the complexities.
Now, several years down the road with many years of experience as a SAS programmer, I still recommend this book to anyone who asks me to point them in the direction of a good book to use for learning SAS.
For beginners, two books better than one .......2003-08-23
I suggest getting both a book like this, for its greater comprehensivity, combined with another one (like 'SAS programming By Example') for its more user friendly accessibility, if you are a beginner. Both books can be used as a starting text, and having two books can be better than one, and each one complements the other.
Good for beginners.......2000-05-14
This is the best introductory SAS book I have seen. It introduces the basic SAS structure and programming statements. A good and detailed explanation is provided for DATA step vs. PROC, a topic that always proves to be difficult to grasp for SAS newbies.
The book starts with SAS terminology and logic, i.e., how SAS works its magic. It moves on to simple tasks such as reading in data, summarizing it, and displaying it. Then there are chapters on SAS programming elements (expressions, logic flows, etc.) as well as intermediate-advanced statements. The MERGE statement is explained very clearly.
Examples abound, although I feel that they are presented in a very confusing format -- often you can't tell if a block of text belongs to the main text or an example. The organization of the book is also a little confusing, esp. if you want to use it as a reference book (not recommended; stick with SAS manual set instead).
In short, this book provides an excellent ovewview of SAS. Read the chapters in sequence and you'll soon be on your way to happy SAS'ing!
A fabulous introduction to SAS essentials.......2000-01-18
If you are in need of data management or analysis, SAS is likely big on your list. This book gives extremely clear and useful introductions to how SAS is structured, how to manipulate and organize data, and some basic statistical procedures (descriptive statistics, ANOVA, OLS models, etc.) are also presented.
Official SAS manuals are usually bulky, complicated, and difficult to understand, particularly if you have little/no experience with SAS. This book can take a complete beginner through data set creation and manipulation into substantially more complex and important procedures and functions. As this is an introduction to the SAS system, the more advanced functions in SAS, such as SAS STAT, are not covered in any detail. However, in order to understand how to actually use SAS and manipulate data so as to employ these higher level procedures, this book is excellent.
This is the absolute best introduction on how to use the SAS system I have seen, but it has lots of useful information for people with some basic SAS knowledge as well. It is presented in the style of a textbook,with each section concluding with problems (with answers provided) that the aspiring SAS programmer can solve.
If you are just starting to look into SAS, I cannot recommend this book highly enough. 'If I was able to do it, anyone can.'
This is a good beginner's guide........1999-08-13
I went to the Fundamentals of SAS course held at the SAS Institute and was left in dire need of more information. This book was a first step. The exercises in the book were helpful and reinforcing. If you need more than brginner's knowledge, then you'll have to purchase another book but this is good to get started.
Book Description
How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Customer Reviews:
Excellent Reference.......2001-06-21
Using this text in conjuction with "Decisions with Multiple Objectives" by Keeney & Raiffa will give you a good application compliment to K&R theoretical work. Bard is geared to the applications. I used both these texts as part of my doctoral course Management Decisions in Engineering at Kennedy-Western University. It is a powerful combination for an in-depth statistical study of Decision Theory & Application.
Average customer rating:
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ASIN: 0131050524 |
Book Description
The objective of this management science book is to help the reader solve the decision-making problems that confront managers in both the public and private sectors. It demonstrates the use of mathematical models to solve these problems, and provides numerous examples and illustrations to help the reader easily understand the material presented. Its concentration on computer solutions with Excel spreadsheets allows the reader to focus on the newest technological tools.
Topics covered in this comprehensive book are linear programming; integer programming; transportation, transshipment, and assignment problems; network flow models; project management; nonlinear programming; probability and statistics; decision analysis; queuing analysis; simulation; forecasting; and inventory management.
With its comprehensive appendices and CD-ROM module examples, this book is an excellent reference work for managers that utilize modeling techniques to solve problems and make decisions.
Book Description
This book is a contemporary introduction to theory, methods and computation in Bayesian Analysis. It focuses on topics that have stood the test of time and emerging areas such as reference priors, objective Bayes testing, Bayesian model selection and wavelets. No other such book is available in the market.
Book Description
Olson's Introduction to Project Management, 2/e is a project management text that focuses on "systems" issues. The primary focus is to examine the many issues facing MIS project managers. The revision also now incorporates the Project Management Institute's Body of Knowledge (PMBOK), better preparing users for the PMI certification exam. Olson focuses on traditional project management topics such as project adoption, planning, scheduling, and implementation while encouraging students to view the projects holistically and analytically. Utilizing the most current software and project management tools, he provides students with the most effective strategies for today's IT project managers.
Customer Reviews:
Weak and Disappointing Introduction to Decision Analysis.......2004-07-18
Overall I think this is a poor introduction to Decision Analysis. The author gives a sketchy explanation of key concepts such as how to draw influence diagrams and decision trees. He emphasis their importance several times, but never gives a thorough explanation of how to create them, with insufficient examples. What is TRULY bothersome is some of the exercises in the early chapters ask the reader to create these diagrams, without the "how to draw them" part ever having been explained!
Other issues I have with this book:
- several typos and grammatical errors
- some of the examples appear to have been "borrowed" from many other (better) books, such as those listed below.
- there is a shortage of concrete examples, and the few examples given are not sufficiently explained. I was not able to follow the analysis process of how to apply some of the concepts explained in the book, specifically on creating influence diagrams
- the author's arrogance is insulting. At the beginning of each chapter he quotes an eminent figure. Some of the quotes come from Einstein, Sun Tzu, Theodore Roosevel. The author has the audacity to put one of his OWN QUOTES in this same space reserved for these other renowned people.
- the author's website, to which he references frequently, was not active every time I checked (last checked July 2004).
- dissapointing explanation of Net Present Value (NPV), an important concept when evaluating consequences of many financial decisions
- very poor explanation of discount rates, another important term
- glossary fails to list important terms, such as discount rate
The writing was OK. The book does provide a mediocre overview to Decision Analysis (DA). The author has apparently worked in the DA field for some time, and refereneces this experience frequently.
As should be evident from my above comments, I am dissapointed by this book. I would have better spent my time spending more money and purchasing a more widely respected text like that of Clemen (listed below). Overall I'd suggest readers avoid this book and instead purchase:
Smart Choices by Hammond, Keeney, Raiffa - very well written, concise book on making better decisions, for the layman. Great examples, thoroughly explained, with useful analogies and applications of the important concepts.
Making Hard Decisions by Clemen - a much more scholarly text used in many Decision Analysis courses.
Hands-on, helpful, comprehensive.......2004-06-03
Skinner covers a lot of territory in this book, hitting important elements of real-world decision-making. I recommend this for new practitioners and managers, or anyone else who wants a comprehensive overview of decision analysis in the business environment. Rather than focus only on number-crunching such as cost-benefit or cash flow projection, he provides an overview (granted, it's somewhat abbreviated) of decision process, scaleability, and decision quality -- topics we don't hear about often enough. For instance, Skinner provides practical checklists and tools such as one for assessing the quality of a decision (p. 96). Additionally, the book functions as an encyclopedia of decision methods, with concise explanations of influence diagrams, Monte Carlo, probability, etc.
A good introduction.......2003-06-03
Skinner presents the tools and applications of decision analysis very clearly. He supplements this with numerous case studies that aid in understanding how to apply these techniques.
This is an introductory text. I believe that the author merely intended to present these techniques. No discussion of their limitations is made. The examples given are very simple, which is very helpful to explain the concepts described in the book. They cannot be expected to address all the issues in a real-life decision problem.
Excellent Introduction to Decision Making.......2003-04-17
This book is very well organized, very easy to read and to comprehend. It must be in your library!!
The Final Chapter: 30' Guide to better decisions, is the perfect closure to an excellent book. It guides you through all the process in a glance.
Very practical, stimulating book.......2001-07-27
This book is a great overview of different DA tools, processes and analyses. The book nicely balances a newbie-level focus with sophisticated forms of analysis.
Skinner's focus is very much on making it possible for readers to take the concepts in the book and immediately apply them to real-world decision problems. Many of the concepts are developed and then presented in a cookbook-like fashion. This style was often clarifying and makes the book an excellent quick reference.
Book Description
This best-selling and up-to-date survey of decision analysis concepts and techniques is accessible to students with limited mathematical backgrounds. It is designed for advanced undergraduate and MBA-level courses in decision analysis and also for business courses in introductory quantitative methods. (Prerequisites: college algebra; introductory statistics.)
Customer Reviews:
Reviewer.......2005-08-25
I am interested in succint yet exhaustive/substantive coverage of the topic for use in real-world corporate finance applications. I found the book to be verbose and not sufficiently to the point. The author peppers a few key insights in endless dialogue, which I find a bit tiresome. The text could be better organized to highlight key points and provide greater substance and less fluff. Definition of terms could be far better written even for an introductory text.
I suspect I am the wrong target audience.
A clear, accessible introduction to an important field........1999-07-23
This is a very accessible book. My classes routinely commend it. It begins by emphasizing the importance of clearly distinguishing between values, decisions and facts. It discusses the need to clarify one's values and then determine the decisions and facts that are relevant. It then discusses sensitivity analysis techniques for identifying which facts are crucial to your analysis. It discusses techniques for deciding when to gather further information. Finally it provides a very accessible discussion of how probability theory can be used to assess your payoff from different decisions. Dr. Robert F. Bordley, General Motors
Studying for an MBA - buy this book.......1999-06-02
A perfect balance for those with mathematical expertise and those without - this book provides a well written and comprehensive view of decision making. Lots of easy to understand and relevant case studies - complete with answers.
I needed to get on top of this subject for my MBA course and, although there is a lot to this subject, in one book there is everything one could possibly need to know.
For corporate decision makers needing to get on top of the subject, this book provides a detailed enough insight to the subject to get started straight away. Its strength is that it is not trying to sell a Microsoft Excel add-in - in fact, it shows how to do without Excel add-ins (although these do make the job a lot easier).
Five stars.
The best available intro to normative decision analysis.......1997-06-06
This is the best book available today for individuals interested in an introduction to normative (as opposed to descriptive) decision analysis. Although it's accessible to readers with minimal mathematical training, it is also very satisfactory for those with more mathematical sophistication, and I use it regularly as a reference in my own professional work. Clear explanations, excellent problems and exercises, and very well-organized. I highly recommend it.
Michael S. Johnson, Arete Consulting, Portland, OR
Book Description
The 2nd Edition of Dr. Winkler's classic book, first published in 1972, includes a CD Rom, Perspectives, and updated material. However, the basic concepts of Bayesian inference and decision have not really changed. This book gives a foundation in the concepts, enables readers to understand the results of Bayesian inference and decision, provides tools to model real-world problems and carry out basic analyses, and prepares readers for further exploration.
Customer Reviews:
Bayesian Inference and Decision.......2005-08-21
This is definitely useful for someone going for an MBA or other managerial degree. I would not have been able to do my class assignment without it. I am taking a graduate course in Statistics and this reference may help me achieve an A.
Get Past The Title... This Is A Key Reference Book.......2003-07-22
Not only is this a top notch instruction tool from a well-respected author, but for anyone whose work or interests lay in the risk and decision analysis field, this is a "must have" reference book. It may seem oxymoronic to say that a book on statistical inference, "probability", or Bayesian methods is interesting, but that is exactly what the author has achieved. Winkler makes what many of us may view to be a complex and intimidating topic understandable and enables practical implementation of the concepts. More than just a simple re-printing, the second edition provides updated references, additional readings and assessments of developments in the chapter scope since the first edition.
The initial chapter in the book provides an introduction to probabilistic thought and Bayes' theorem. Following chapters deal with discrete and continuous distributions, decision theory (practical applications...including influencing factors such as utility and subjective probability), Value of Information, and Bayesian approaches to hypothesis testing (quite meaningful for six-sigma thinkers, efficient resource appraisal decisions, and other business applications).
Practitioners will have to get past the rather academic title. If you model or work with uncertainty distributions, dependency, correlation, or contingent portfolio analysis, this book will provide the necessary conceptual understanding that will save you time and allow you to provide a better, more valid product.
The CD that accompanies the book provides standard reference tables and work-throughs for many of the problems/examples. All figures found in the book are included as are all chapter exercises (MS Word format). It also provides trial versions of decision software such as Lumina's Analytica (object based simulation) and TreeAge's Data (decision trees). A series of distribution generators are included as a plus for those of us who have a simulation modeling bent.
There is folklore that is tied this title. So well received was the first edition that rumors persist regarding people resorting to beaten up photocopies of the book. You don't have to do that anymore.
Book Description
About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.In this new and expanding area, Tony Lancaster 's text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.
Customer Reviews:
Good book!.......2007-04-12
I'm taking an intro to Bayesian stats class and we are using the Carlin & Louis book -- it is a POS.
I found this book in the library and it is much better. It gives very clear explanations of the ideas, and lots of concrete worked examples. Props to the author.
Clear as crystal and plenty of workouts.......2006-07-25
This is as clear as crystal. It also has plenty of workouts. It is a very useful volume.
Great Book.......2006-03-19
If you are looking for a book for Bayesian estimation, this is the one. The first several chapters say it all about Bayesian methods. The rest of the book is applications. Very helpful reading for learning the method.
Book Description
Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee's classic introduction maintains the clarity of exposition and use of examples for which the text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS, as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modeling and Bernardo's theory of reference points.
Customer Reviews:
a review.......2006-09-17
This book has a clean selection of materials as an introduction to bayesian statistics. It is quite readable. Two problems however: 1) the formula derivation and reasoning often have intermediate steps skipped. You need to think for a while for derivations and his texts. In particular, you need to figure out by yourself which theorem or previous results that the derivation is based on. 2) typos. the 3rd printing still has typos not listed in the author's page, not too many but not trivial either.
Anyway, I still recommand this book because no better introductory bayesian book found yet.
good intermediate text.......2002-09-10
Although only the second edition is listed, I have read only the first 1989 edition and my review is for that edition. Lee wrote this book with the goal of teaching an introductory course in Bayesian statistics to his students at York University. He wanted a text that was more mathematical and deatiled than Lindley (1965) but not quite at the level of Box and Tiao.
This text achieves that goal. It was published at the time when MCMC methods were only starting to be appreciated. So the wider use of general prior distributions and hierarchical models does not yet enter into this book. I would assume that the second edition published in 1997 was written to remedy this shortcoming but I have not seen if it does.
Good introduction to basic theory of Bayesian statistics.......2001-12-05
This is a simple and easy-to-read introduction to the basics of Bayesian statistics, for someone with some previous exposure to statistical methods and theory. Lee does not try to do too much with this book. It's not too taxing on the brain, uses simple and easy-to-follow notation, and has a helpful appendix of common statistical distributions. I like the emphasis on conjugate priors, which are the mathematically most tractable Bayesian models that are often not treated fully in other texts. (Someone still needs to write the definitive text on conjugate Bayesian models.)
The book is limited in scope, a strength if you're just getting started on this topic, but will frustrate once you get into this stuff. There are plenty of other good books that go beyond the basics once you're ready.
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The Little SAS Book: A Primer, Third Edition
SAS Programming by Example
Cody's Data Cleaning Techniques Using SAS Software
Handbook of Statistical Analyses Using SAS, Second Edition
Longitudinal Data and SAS: A Programmer's Guide
