Book Description
This classic text on multiple regression is noted for its non-mathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for a solid understanding of the rest of the text.
The third edition features an increased emphasis on graphics and
the use of confidence intervals and effect size measures and an accompanying CD with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT.
Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters. The book is an ideal text for courses on multiple regression and correlational methods.
Customer Reviews:
Second Grad Stats.......2007-05-06
I've adopted this text for my graduate seminar in Multiple Regression. I choose it over other texts for the topics AND because it's focus is on concepts rather than math. Now that we can carry SPSSX in our brief case, there is no need to focus on that computation.
Can't beat it.......2001-04-17
...This book is the source of all you need. It's hard going at times, but so's the subject. The book's 15 years old and remains the best guide to the analysis of correlated data. It's a reference book, one I value as much as a good dictionary. To use it as a text would be misguided unless the instruction was aimed at a sophisticated audience.
Best MRC Book Ever.......2000-03-24
I agree with the previous reviewer that there are times when the exposition in the book gets a bit intense; but c'mon! We're dealing with statistics. You gotta sweat a bit. That's when learning happens. In my opinion the book is extremely clearly written. And although you may have to re-read a few sentences a few times, the basic tools for understanding most every major aspect of MRC is embedded in the text. In sum, this was a great book that I read as a 2nd-year graduate student in psychology. Unlike the first reviewer, I turned to this text when I got confused during the course lectures!
MRC Analysis---good book overall.......1999-12-15
Cohen and Cohen's MRC analysis book is well versed and easy to understand for someone that is familiar with MRC terminology, however, for first year graduate students, the text is very equivocal. The book is lacking ample illustrations of complex problems, leaving students to rely on outside sources. Also, the book uses unfamiliar symbols that do not correspond with other MRC books, which intensifies the confusion level of the students even more.
Overall, the text is a great addition to a statistical library, and this reviewer recommends it, in spite of being a sub-par book for first year graduate students.
Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Customer Reviews:
Fantastic!.......2007-09-26
Just wanted to add to the praise of this book. If you're not following the backtesting practice of this book then you're playing slots with your trading (hey, maybe you'll get lucky!!). Some of the material is tough going and will require a second reading, but it'll be worth it. As another reviewer said about this being a kind of in-depth follow on to "Fooled by Randomness", I couldn't agree more. As matter of fact it's what I read just prior, so I couldn't help smiling as I went through this book, because he was putting the meat on the plate that Nassim set! Thank you, thank you..
The previous reviewer (Useless..) that gave it one star clearly did not get the concepts of the book. Did he even read it? That review does not compute. The *only* negative I would say is that if you're just looking for how to do robust backtesting, then the extensive material on the scientific method might be a bit much (but you can always read lightly those sections). But I understand why he put it in there, since it's the entire premise of taking a different and more rigorous approach to TA.
Now back to re-reading Chapter 6... Thank you Mr. Aronson!
Useless.......2007-08-29
I found this book useless..a total waste of time and money.Instead of analyzing the results obtained by using the various technical indicators,the author simply trashes their use,and does so in a preverse use of mathematical formulas,from which the reader gains nothing.I truly felt like my money was taken,for the purchase of the book,under false pretenses.
Make backtesting meaningful.......2007-08-24
Most trading books are pseudoscience or entertaining reminiscences of successful traders. Aronson has done an admirable job of applying the requisite rigor to the many difficulties associated with analyzing the results of historical backtesting.
Best for professional, intellectual and philosophical trading system developers.......2007-08-08
I had thought of using another review title "For fans and followers of Victor Niederhoffer" as inspired by his praise on the front cover. Pardon me to assume the following: if you had not heard of Niederhoffer, the chance is high that you have no prior experience/idea of testing the statistical significance of various TA tools, nor dwelling into the philosophical/scientific aspects of TA at all. Please accept the fact that this book is not for you. For trading professionals who deem themselves philosophical and intellectual (preferably with a college level of knowledge on statistics), this book is an inspiration. Highly recommended!
A must-have for TA practitioners.......2007-08-01
This book shakes some of your most deep beliefs in TA - and this is a healthy thing. Read it with an open mind.
Average customer rating:
- Legendary and masterpiece in estimation theory
- couldn't rate 6... a must !
- A reference for self-directed study
- The book has depth and is well written
- An Excellent Book in Estimation Theory
|
Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory
Steven M. Kay
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Similar Items:
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Fundamentals of Statistical Signal Processing, Volume 2: Detection Theory
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Statistical Digital Signal Processing and Modeling
ASIN: 0133457117 |
Amazon.com
This text is geared towards a one-semester graduate-level course in statistical signal processing and estimation theory. The author balances technical detail with practical and implementation issues, delivering an exposition that is both theoretically rigorous and application-oriented. The book covers topics such as minimum variance unbiased estimators, the Cramer-Rao bound, best linear unbiased estimators, maximum likelihood estimation, recursive least squares, Bayesian estimation techniques, and the Wiener and Kalman filters. The author provides numerous examples, which illustrate both theory and applications for problems such as high-resolution spectral analysis, system identification, digital filter design, adaptive beamforming and noise cancellation, and tracking and localization. The primary audience will be those involved in the design and implementation of optimal estimation algorithms on digital computers. The text assumes that you have a background in probability and random processes and linear and matrix algebra and exposure to basic signal processing. Students as well as researchers and practicing engineers will find the text an invaluable introduction and resource for scalar and vector parameter estimation theory and a convenient reference for the design of successive parameter estimation algorithms.
Book Description
A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms.
Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems.
MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.
Customer Reviews:
Legendary and masterpiece in estimation theory.......2004-06-13
Without any hesitation, I consider this book as a masterpiece in the area of statistical signal processing. Kay takes the reader to the journey of estimation theory as if a science teacher takes his students to a field trip. The one special feature of this book is the convergence of thought that reader obtains upon reading the book. Kay lays a fundamental bridge between various estimators using his succinct style for describing the subject.
Few special areas require more attention in this book. For example the coverage of EM methods is very condense and requires more elaboration. Also there is no discussion on the estimation methods using higher order statistics.
Overall I consider this book as the best book I have read ever and I highly recommend this book to those who want to obtain an ever-lasting view on statistical signal processing.
couldn't rate 6... a must !.......2003-08-12
I've had tough courses on statistical signal processing as a post-grade student. I am often confused in front of a problem and turning back to the notes taken in class doesn't help much.
When you read this book all gets bright. I am still wondering how some teachers can be so confusing while such good books do exist...
However don't count on it for in depth mathematical demonstrations, it starts with a practical problem and explains how to model things. Thus it is a bit bottom-up but anyway starting from a good graduate level in signal and stats.
I got this one at the library but already ordered a copy for myself and am planning to get part2 on detection.
A reference for self-directed study.......2003-06-09
This text is very good for those who start doing research in statistical signal processing. A lot of explanations, technical terms are well presented and consistent, plus a number of examples that help you to learn about different statistical signal processing concepts and algorithms. Research students can be beneficial alot from this text.
The book has depth and is well written.......2003-02-08
This is one of the best references on statistical signal processing. The topic is not of simple matter, but the author presents the materials clearly together with great examples. The book is reader-friendly and is relatively error-free. I have bought several copies for my PhD students at Georgia Tech.
An Excellent Book in Estimation Theory.......2002-03-04
This book was asigned to me for a graduate course in Statistical Signal Estimation. The book was very useful and easy to read. It was well written and had helpful examples. I recommend this book for any one who wants to learn about Estimation Theory.
Book Description
"This is a first-class book dealing with one of the most important areas of current research in applied statistics…the methods described are widely applicable…the standard of exposition is extremely high."
--Short Book Reviews from the International Statistical Institute
"The new chapters (10-14) improve an already excellent resource for research and instruction. Their content expands the coverage of the book to include models for discrete level-1 outcomes, non-nested level-2 units, incomplete data, and measurement error---all vital topics in contemporary social statistics. In the tradition of the first edition, they are clearly written and make good use of interesting substantive examples to illustrate the methods. Advanced graduate students and social researchers will find the expanded edition immediately useful and pertinent to their research."
--TED GERBER, Sociology, University of Arizona
"Chapter 11 was also exciting reading and shows the versatility of the mixed model with the EM algorithm. There was a new revelation on practically every page. I found the exposition to be extremely clear. It was like being led from one treasure room to another, and all of the gems are inherently useful. These are problems that researchers face everyday, and this chapter gives us an excellent alternative to how we have traditionally handled these problems."
--PAUL SWANK, Houston School of Nursing, University of Texas, Houston
Popular in the
First Edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been reorganized into four parts with four completely new chapters. The first two parts, Part I on "The Logic of Hierarchical Linear Modeling" and Part II on "Basic Applications" closely parallel the first nine chapters of the previous edition with significant expansions and technical clarifications, such as:
* An intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication in Chapter 3
* New section on multivariate growth models in Chapter 6
* A discussion of research synthesis or meta-analysis applications in Chapter 7
* Data analytic advice on centering of level-1 predictors and new material on plausible value intervals and robust standard estimators
While the first edition confined its attention to continuously distributed outcomes at level 1, this second edition now includes coverage of an array of outcomes types in Part III:
* New Chapter 10 considers applications of hierarchical models in the case of binary outcomes, counted data, ordered categories, and multinomial outcomes using detailed examples to illustrate each case
* New Chapter 11 on latent variable models, including estimating regressions from missing data, estimating regressions when predictors are measured with error, and embedding item response models within the framework of the HLM model
* New introduction to the logic of Bayesian inference with applications to hierarchical data (Chapter 13)
The authors conclude in Part IV with the statistical theory and computations used throughout the book, including univariate models with normal level-1 errors, multivariate linear models, and hierarchical generalized linear models.
Customer Reviews:
pre-req: mid-level stats experience.......2006-07-12
I had taken a class in HLM before, and I bought this book to refresh myself on the details. It takes a good deal of attention to detail and concentration to really get the full measure from this book, although it's all in there. Despite the authors' best efforts, there is a good bit of stats jargon in the book, so a reader who is not familiar might have some difficulty. If you're at a point where learning HLM is a logical next step, you'll be fine and I recommend this book. However, if your over-eager faculty advisor told you to learn HLM, despite your minimal experience in stats, you're better off enrolling in a class or workshop.
Good but sometimes skipping ahead too fast.......2006-03-09
This book gives a detailed description of the use of an advanced method to deal with nested data sets.
At a general level the constructs and ideas are well written and can be followed reasonably easily.
However the mathematics is often written very dense, which makes reading and understanding complex.
My main problem with the book, is that in many of the examples they provide, the given formula's, and data skip rapidly to the solution. Thus it is often not insightfull at all, how the data led to the numerical outcome (and I and several of my colleagues could not reproduce all of the example outcomes). A more extensive discussion and a more step-by-step construction of the examples would have been helpful there.
So in short: Conceptually this book is fine, but for practical use mathematics are too dense, and examples are too hard to follow
Useful, but need solid background in stats.......2004-06-05
This book describes important advances in statistical analysis of social science data, circa 1992. Much of this data has a natural hierarchical grouping. But traditional statistical methods proved inadequate at coping. The biggest drawback was the failure of the assumption of independence. If at the lowest level, Items I1,...,In are grouped into sets J1,...,Jm, where m
To handle this, Hierarchical Linear Models were developed. The book gives a detailed treatment. A very comprehensive discussion. Including the handling of meta-analysis, where we wish to combine results across different studies. Which then involves using empirical Bayesian estimates. This method has also seen important usage in evaluating medical studies, conducted by different researchers on the same topic.
The book also illustrates the essential development of non-trivial computer programs to perform the gruntwork.
You will need a solid background in statistics to find this book useful. At a minimum, a year of statistics at the undergraduate level.
Book Description
Robert J. Lang, one of the world's foremost origami artists and scientists, presents the never-before-described mathematical and geometric principles that allow anyone to design original origami, something once restricted to an elite few. From the theoretical underpinnings to detailed step-by-step folding sequences, this book takes a modern look at the heart of the centuries-old art of origami.
Origami novices will appreciate the organization of the book, which begins with easy techniques and progresses to deep and powerful tools for design, all based on simple, intuitive concepts like grafting, circle packing, and assembly of tiles.
Both novices and aficionados will find detailed, step-by-step instructions for previously unpublished models, including the famous "Black Forest Cuckoo Clock."
Customer Reviews:
Not an origami recipe book.......2006-01-13
Dr. Lang delves into the hows and whys of origami design exploring origami the way Alton Brown explores food and cooking.
The instructions for creating beautifully made koi decorating the cover are not included in their entirety, notably excluding the sequence for creating the scales. Instead, Lang describes the principles and techniques for creating textures on paper, leaving the creation of the fish as an exercise for the reader.
If you're looking for a recipe book for cool origami designs, then this is not the book for you. Rather, this book is for anyone curious about just how the heck someone makes a cuckoo clock out of one uncut sheet of paper.
A truly incredible book!.......2005-09-28
By far and away the most comprehensive book on origami design and theory that I have every seen. There are thousands of books containing origami models, but few, if any, actually take the time to explain how the models were created in the first place. If Robert Lang didn't already hold a Ph.D., this book could serve as a dissertation. In addition to the theory and concepts of origami model design, this book also contains excellent models that demonstrate the principles covered in each chapter. I have always enjoyed folding Robert Lang's models in the past. They are challenging and extremely rewarding. I am a very good techincal folder but I could never really create my own models. This book has started me on my own path towards creating my own origami models to fold. While this book certainly could be useful to beginning origami folders, it best serves intermediate to advanced enthusiasts.
A great origami book.......2005-09-28
This is one of the best origami books ever written. Robert Lang is known for producing complex origami models and here he teaches the mathematical thought process behind the creation of these pieces. The book contains a number of chapters covering different methods of producing particular types of origami works and then each chapter ends with a series of advanced origami models for you to make with complete diagrammatical instructions.
The book is a wonderful instruction manual on how to create original origami designs but it also includes many sets of instructions for origami models which have never before been published. The exquisite Koi carp on the front cover (which I have seen in real life) is included as is the frog, and the infamous Black Forest Cuckoo Clock instructions are included at the end of the book. Don't try to make these pieces with ordinary paper - you will want to use very fine bank weight paper, tissue foil or wet folding with Canson or Elephant Hide paper to get good results.
This volume is an essential addition to any paperfolder's bookshelf and will provide many hours of interesting reading and wonderful models to fold.
The one book that every origami fan MUST have!.......2004-12-08
Robert Lang's book is one of the most amazing origami books I have ever seen. Disregard the higher than normal price for the book, it is worth every penny.
People who are simply interested in folding models will be delighted by the awe-inspiring Black Forest Cuckoo Clock and the collection of turtles (complete with shell designs). Other models include birds, a moose, a train, a valentine heart, and many, many others...all out of one sheet of paper with no cutting.
The books real value, however, is its wonderful discussion of the origami design process. Lang breaks down many different aspects and techniques of design into understandable bites. Personally, I enjoyed the mathematical discussions throughout, especially the tree theory section.
The bottom line: (out of 10)
---------------
Model Value:
9 (not a book entirely of models, but the models that are contained are gorgeous)
Instruction Clarity:
9 (excellent considering how complicated the models are)
Difficulty:
10 (even origami pros will be challenged by the clock and the tiling of the fish and turtle)
Enjoyment:
10 (reading the book is as gratifying as actually reproducing one of the models within it)
Overall Value (not an average):
10 (a true masterpiece)
The key to understand Robert Lang's work.......2004-10-12
If you are like me, at some point you developed an interest in Origami and your attention was caught by Robert Lang's books. I bought "Origami Insects and their Kin" and was immediately fascinated by the lifelike and ingenuity of the models. My fascination became frustration when I tried to find any model in the book that was "doable". With much patience, wasted paper and a few suicide attempts :-), I finally did one - the ant ! I kept coming back to the Praying Mantis and the Pill Bug with no luck. Then I found this magnificent book - Origami Design Secrets. By studying the methodology created by Dr. Lang, one can see the method behind his genious (or madness :-). I was stumped by a sequence in the Praying Mantis, then I understood what was behind it once I read the chapter on "splitting"... It was like a revelation! The presentation of this book, the didactics and the clarity are superb. Dr Lang created a whole new field of science to explain Origami. It also helps the creative process and the goal to eventually create your own models. I will never be a "virtuoso" like Dr. Lang, but this book opened a whole new set of doors for me. I highly recommend it!
Book Description
Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: BL Downloadable data sets BL Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more BL Additional material for data analysis
Customer Reviews:
A Wonderful Work.......2007-07-15
I find Professor Singer's Book to be a most informative and useful tool for anyone who wishes to better understand Multilevel Modeling.
Applied Longitudinal Data Analysis by Singer,et al.......2007-03-13
Clearly written text... and usefull for researchers.
I would recommend it to anyone starting to learn about the subject!
The Clearest and Most Useful Book on HLM for Longitudinal Studies.......2006-07-28
This is simply the best book for those analyzing longitudinal data (data measured at more than one time point). Singer's coverage of Hierarchical Linear MOdeling (HLM) is clear, well-written (sprinkled with humor, it's like a lecture by the most popular prof. at your school), and geared towards researchers who need their programs to run, not just learn the mathematical underpinnings. Singer and Willett (the coauthor, not listed above!) set the standard for presenting math/statistics book examples.
THe authors accomplish the latter by keying her examples to data located at a UCLA website; you can run the same programs on the same datasets used in the book (wow!), and compare your output, troubleshooting any problems you may have. Singer and Willett (her coauthor, not listed here!) provide outputs and programs correspoing to several of the most popular statistical programs, including SAS and SPSS.
SInger and Willet also explain the rationale for using HLM over more traditional techniques such as regression. Simply stated, regression aggregates at a level that cause one to lose information (and hence the power to detect differences.) HLM allows one to look at overall differences due to time, but also the trajectories of individual differences who are "nested" within those time points. It's the (relatively) new thing, and is increasing used by investigators, and desired by peer reviewers.
As supplements, I suggest using the UCLA website mentioned above, subscribing to an e-mail LISTSERV for interesting (though sometimes compicated discussions of "multilevel modeling" (MULTILEVEL@JISCMAIL.AC.UK), and searching for Judith Singer's website through Google or A9 (if you use A9--"Alexa"--enough you'll get a small discount at Amazon.com). Also, compare Amazon's and Judith Singer's (through her website) current prices on this book.
Breaking down complex analyses .......2006-03-18
This is an excellent book. Multilevel modeling and survival analysis are becoming increasingly important in psychological studies, but are pretty complicated procedures. Singer & Willet offer both a conceptual background and practical ways to do the analyses in a clear, understandable manner. The book is very readable and will be an important reference for future analyses!
very clear and thorough.......2006-03-16
This book does a particularly good job of explaining the substantive meaning of the equations involved in multilevel modeling analyses. It spends a lot of extra time explaining what the equations mean in real world terms using examples from actual data sets. I teach a graduate level course on HLM and I much prefer this book to the Raudenbush & Byrk book because it not only does a better job of explaining the math (for graduate students less comfortable with statistics) but the chapters are also sprinkled with incredibly useful advice on actually running the analyses (getting them to converge, interpreting them, etc.) The Raudenbush & Bryk book probably does a slightly better job of presenting the equations, but it falls short on explanation and practical advice. If you were only going to buy one HLM book, I would start with this one.
Book Description
Still brief - but with the chapters that you wanted - Steven Chapra’s new second edition is written for engineers and scientists who want to learn numerical problem solving. This text focuses on problem-solving (applications) rather than theory, using MATLAB, and is intended for Numerical Methods users; hence theory is included only to inform key concepts. The new second edition feature new material such as Numerical Differentiation and ODE's: Boundary-Value Problems.
Book Description
Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques.
This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios.
The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.
The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.
Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."
Customer Reviews:
Review for Monte Carlo Methods... by P. Glasserman.......2007-07-16
The book is just right for a reader who is looking for state-of-the-art techniques in Monte-Carlo methods in general. The fact that the book is specific to financial systems does not limit the usability of the book in the manner it is written. There are a lots of useful references one can get out of this book.
The book is for advanced readers in the sense that it requires rigorous mathematical ability to understand all the concepts. It is by no means for a novice reader and requires background in computational mathematics.
Best financial engineering book on MC.......2007-06-29
This is like the bible of Monte Carlo methods in financing. Both a good read and a good reference book. Must have! for any quant on wall street.
good book on Monte Carlo in Finance.......2007-04-02
But it seems the author is a little focused on selling his ideas, but not a very subjective overview of all topics in M-C method in finance.
Excelent choice on finance Monte Carlo.......2007-03-08
Clear and sound theoretical background on applied Monte Carlo for finance.
Brilliant.......2006-12-26
Almost everything related to Monte Carlo in Financial Engineering is covered at just the right level of detail. Quite easy to read too.
Average customer rating:
- Very Practical Book
- Good for first edition
|
Applied Statistics For Engineers and Scientists Using Microsoft Excel and MINITAB (With CD-ROM)
David M. Levine ,
Patricia P. Ramsey , and
Robert K. Smidt
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ASIN: 0134888014 |
Book Description
This applied book for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software complete this treatment of statistics.
Chapter topics include describing and summarizing data; probability and discrete probability distributions; continuous probability distributions and sampling distributions; process control charts; estimation procedures; hypothesis testing; the design of experiments; and simple linear and multiple regression models.
For individuals interested in learning statistics—without a high level of mathematical sophistication.
Customer Reviews:
Very Practical Book.......2003-11-30
I have found this book to be very useful with practical examples and case studies. I felt that as an engineer I needed to know how to use software(to save time)along with the formulas that work in it.This book satisfies that, using a very common software EXCEL..what could be better than this.
I strongly recommend this book for a high level course in statistics.
Good for first edition.......2002-05-10
I used this textbook for a course in statistics. I must say that it was better then the first time that I had taken statistics 5 years ago. The book uses one or two data sets per chapter that helps you focus your thoughts while learning the different techniques. A nice feature about this book that wasnt available 5 years ago is the Excel and Minitab examples which saves a lot of time that is ordinarly spent on copious number crunching. I would have given the book 5 stars, however I found some obvious errors in the book that should have been edited out before the release. Good starter book for sats.
Average customer rating:
- Great introduction to mathematical economics!
- A must read text book for any economics undergrad student
- A must read for graduate students in economics
- not so good
- The best math textbook for economist
|
Fundamental Methods of Mathematical Economics
Alpha C Chiang
Manufacturer: McGraw-Hill/Irwin
ProductGroup: Book
Binding: Hardcover
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Similar Items:
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Schaum's Outline Introduction to Mathematical Economics
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Mathematics for Economists
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Microeconomic Analysis, Third Edition
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Advanced Macroeconomics
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Econometric Analysis (5th Edition)
ASIN: 0070108137 |
Book Description
The best-selling, best known text in Mathematical Economics course, Chiang teaches the basic mathematical methods indispensable for understanding current economic literature. the book's patient explanations are written in an informal, non-intimidating style. To underscore the relevance of mathematics to economics, the author allows the economist's analytical needs to motivate the study of related mathematical techniques; he then illustrates these techniques with appropriate economics models. Graphic illustrations often visually reinforce algebraic results. Many exercise problems serve as drills and help bolster student confidence. These major types of economic analysis are covered: statics, comparative statics, optimization problems, dynamics, and mathematical programming. These mathematical methods are introduced: matrix algebra, differential and integral calculus, differential equations, difference equations, and convex sets.
Customer Reviews:
Great introduction to mathematical economics!.......2007-07-18
I enjoy Chiang's writing style. I've been reading up on mathematical methods in preparation for a masters econ program, and feel very comfortable with the material thanks to this textbook. The international edition is a good bargain.
A must read text book for any economics undergrad student.......2006-04-02
I found it extremely easy to read and at the same time rigorous enough to settle the bases. The author knows very deeply the economics students needs of mathematical methods and achieves a precise and complete explanation of all notions I needed to know for my undergrad course. I strongly recommend it during the first or second year.
A must read for graduate students in economics.......2006-02-26
Alpha Chiang's text should serve as the foundation for all quantitive analysis done in economic theory. It is an invaluable teaching tool for graduate students in economics and will help them better understand the mathematical techniques that have become so necessary for economic modeling.
I am not a highly quantitative person myself, but I found Chiang's book comprehensible and a useful reference guide in my gradaute economics classes. Along with Hal Varian's "Microeconomic Theory" and Jan Kmenta's "Econometrics", I would say that Chiang's "Fundamentals of Mathematical Economics" should serve as sacred literature for any prospective graduate student in economics.
not so good.......2005-10-14
the text carries to excess the concept of "keeping the presentation as simple as possible". but in general you cannot understand or solve problems with a fifth grader's ability to abstract them.
especially the relunctance to use matrix notation makes some topics actually harder to understand once they become more complicated.
furthermore I find the structure quite confusing since the text amounts to a monotous blabla - clear definitions might be helpful and some rigor would keep the reader conscious instead of drifting off. after all the text is not so bad but I think we deserve something better. blume might be better.
The best math textbook for economist.......2005-09-30
That is why it used everywhere, in nearly all economic departments. I strongly recommend you buy this book. It really helped me in my undergrad, and it is helping in my graduate courses. If you want to buy another book to accompany this, get Simon and Blume book. One person (probably little masochistic) was saying that Chiang has so many examples, blah, blah, blah. Look, not everyone is a math genius, undergraduate student's need Chiang, it's even useful for graduates. Math is used quite too excessively in economics...showing off?
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