5 comments about College Algebra (Lial/Hornsby/Schneider Series).

1. I'm getting ready to take Intermediate Algebra using a text by this author. I will be required to take College Algebra next term and am hoping, after reading your reviews, that this is NOT the book that will be required for the class. Did anyone get value from "math help" websites? Thanks!



2. This text is a pathetic excuse for educational material. It gives meager examples and many are not even applicable to the chapter exercises. By far this is the poorest written text I have encountered in three years of college.



3. I am by no means a math wizard. I am, however, able to learn things on my own fairly well. This book makes that nearly impossible though. This book gives very few examples, and the few that they do give rarely give any clues to what needs to be done to solve the equations. It also fails to really teach anything. It's by no means for a student that is going to be going through an online course where they won't be interfacing with an instructor. I would not have enrolled into the course for online schooling if I had know this books was going to be this terrible. I strongly don't recommend this book!!!



4. I am teaching from this book this summer, and I have not had the problems that other reviewers have described. This book is written for people with a pretty good understanding of high school algebra - after all, it is a college algebra book. It is not watered down at all, and the material is presented in some depth. However, I have found that this book does a really good job of warning students about common mistakes. I have found it clear (I can't say that for every algebra book I've used.) and my students have not complained, either. I would use this book again.



5. If you're hoping to do well in your mathematics course or just learn math on your own time, you've chosen the wrong book.
   
   The sections provide very little lead-in, and are filled with a few examples, which may or may not help you do the homework problems at the end of the section. Many times you will find formula notation different from the standard that all other textbooks use, so if you move onto the next level of math, you will see entirely new (Easier) ways of learning the material.
   
   This book only works sufficiently if you've been through precalculus/calculus sequence already and are looking for just a quick cheap refresher on some algebra, which is probably why it is appealing to college professors. If purchasing a different book is an option for you, go for Blitzer or Larson's Precalculus text.

5 comments about College Algebra (4th Edition).

1. Very much liked the review of the prerequisite math rules needed to make progress with algebra. Good examples, good practice problems.



2. If you take the time to read the book it is engaging and sometimes funny. The author explains the math very well using real-world situtations. The application problems are great for bringing the concepts home.



3. Received via UPS in couple of days. Book was in perfect condition. Couldn't believe it was used. Saved lots of money.



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5. this covers the basics first and then goes on to of course the harder stuff. It is a good book. I received it soon after ordering and it was a great price for such a "good-looking" used book.

5 comments about Schaum's Outline of Advanced Calculus, Second Edition.

1. If you are studying calculus, the books from Schaum will certainly help you to develop your problem solving ability.
   
   This is NOT a real analysis textbook inspired on Bourbaki topology. So that some readers do not consider the material really advanced. I think they were expecting 18 ways to express the Axiom of Choice (Zorn Lemma for example) Godel conjecture, Fixed point theorems, path and non-path conected sets, differential forms, more terminology (homeomorphism, diffeomorphism, manifolds) etc...
   
   The book has an approach similar to Piskunov or G.B. Thomas Junior books, that is, more elementary approaches (but note that elementary does not mean easy). Many solved problems.
   
   Look at table of contents inside the book at amazon to grasp an idea of what you will get.
   
   Overall, very good companion, practical and with many examples.



2. I don't know about you, but I buy Schaum books so I can have a large number of problems to work with answers so I know when I'm doing it right. My great frustration is people who say "don't look at the answers or you'll never learn the material". BS. That's fine for people with good highschool math preparation, but when you're striving to overcome the legacy of miserable math teachers in US public schools, it fails miserably. I can spend hours on a problem and still not get it. I think the problem for people like me is that we just don't know the language or know how to think about mathematics. Hence I'm giving the book 1 star. I'm looking for a supplement to an obtuse text for an advance calculus course, not another obtuse text.



3. Son came home one weekend and announced he was failing his college calculus course. We purchased this book for him and he is now getting A's......to be honest though.....don't know for sure if it's the book or our threaat to terminate his weekly allowance if he failed.....think it's probably both.......and son says the book has helped.



4. I have taken extensive coursework in undergraduate calculus, advanced calculus, and a 2-semester real analysis course with Rudin's 'principles.' This book was incredibly helpful to me, because it provides some examples of material that Rudin covers, and these examples helped me gain a better understanding of the material (there are 1370 solved problems!). There is nothing in this book about topology per se, but it does cover just about everything else: numbers, sequences, limits/continuity, derivatives, integrals, partial derivatives, vector geometry, multiple integrals, line integrals, infinite series/products, improper integrals, Fourier series & integrals, and gamma/beta functions. This book shines in the plethora of material covered, and because it focuses on solving difficult problems as opposed to routine ones. Another thing is that this book DOES include most of the answers to the supplementary problems - answers are only omitted, for example, when the question says to prove something (prove that the series converges, etc). My analysis professor *loved* improper integrals, so the chapter on that was especially helpful. This text also includes Dirichlet's test for series, which is left out of Rudin. There are a few minor typos that are easily spotted, but for $20 these mistakes can be overlooked. Overall a great reference with many helpful solved problems: A+



5. The proof of Leibniz theorem on p.194 is completely wrong.
   The proof uses the mean-value theorem for derivatives, not integrals, and needs uniform continuity to complete.
   There are numerous typos, including the preface.

5 comments about Fractals, Googols, and Other Mathematical Tales.

1. This book explores a wide range of mathematical concepts, including many of the traditional "fun" topics like Fibonacci numbers. For each topic (covered on two large pages typically) there is a simple story written to be accessible to even young children, followed by a franker and more mature mathematical discussion. This two part approach makes the text accessible to a wide audience while having a solid mathematical foundation. The articles serve as a solid foundation to spark student interest in further exploration, or stand alone as interesting mathematical shorts. Some of the topics will have direct curricular applications, including articles on the real number system and the transcendental number pi. This is a wonderful text and is suitable for elementary through high school students.



2. I was disappointed. While skimming through the book prior to giving it to my 7 year old son, I stumbled on the Chapter on "PI". It was obviously wrong stating that the diameter of a circle would wrap around the circle "3 and a little bit". Now, how can I trust this book knowing that the editors missed such a glaring error? Could be very confusing to a young aspiring mathmetician.



3. I am not sure what R. Krapf "Engineer" (below) was thinking when he/she wrote his/her review...
   
   The circumference of a circle (C) is calculated as 2 * pi * r (or pi * 2 * r)
   
   Since r is the radius and 1/2 the diameter (d), that means C = pi * d
   
   Since pi is about 3.14, that means the book is correct. The diameter of a circle would wrap around (the circumference of) the circle "3 and a little bit"



4. I believe the quote about the circumference and diameter is worded incorrectly. We all know that the size of the diameter and circumference are proportional (hence pi), but the diameter would never wrap around a circumference 3 and a little times! This is obviously false because the circumference is larger than the diameter. The circumference would wrap around the diameter 3 and a little times. Please check your books to determine if the quote is correct in R. Krapf's review - if so, then the book is WRONG!



5. C=pi*d. That means the diameter has to be **multiplied** by "three and a little bit" in order to be equivalent to, or wrap around, the circumference of the circle. It takes "three and a little bit" diameters to get around the circle one time, not one diameter to get around the circle three and a little bit times. The engineer was right! Other than that, it was still a pretty good book, though. If you're a teacher with an older class, you can see if they can spot the error.

5 comments about Introductory Statistics with R (Statistics and Computing).

1. If you have learned the stat concepts behind these procedures already, this is book is great. I think this book is very helpful for people who have had a few stat courses where the professor used a competing stat software package.
   
   I really like how the author repeats some of the important syntax explanations throughout the book (for example, why attaching a data frame makes the syntax more concise). This approach makes it better than trying to learn R from the isolated html help files.



2. I bought this book a little over a year ago when a friend and colleague insisted I learn the R system for our collaborative work. I am not a professional statistician, but an engineer and researcher who needs and uses statistics in the course of my professional work.
   
   I found this book approachable and informative from the non-professional perspective. (That is, from the viewpoint of a non-statistician.) I found enough examples to guide me through the process of bringing my datasets into the R environment, and then enough guidance to get me through the initial analyses necessary to make meaningful use of the statistical computations contained within the R system.
   
   There are many other texts that treat the kinds of advanced statistics capability in the R system. Those are also necessary references for the non-statistician. There are also other texts on using the graphics subsystem present in R (which is substantial). Those references are also useful for preparation of reports and other written material.
   
   But, this text is most useful as a primer for the system and is a first source on my shelf when I need to know the "how-to" of the basics. Then, if my needs are more substantial than those addressed by Dalgaard, I'll turn to other references.



3. The shipping is fast and the book arrived in good quality. I appreciate it very much. Thanks!



4. If you are new to statistics or have a limited knowledge of basic programming skills this book is not for you. If you understand basic statistics and know something about programming then this is an excellent introduction to how to use R to perform basic statistical analysis. It is not an R manual, as was stated in the preface. Nor is it an introductory statistics book by itself. It describes the analysis technique in high level, walks through the analysis step by step, and shows you how to use R to do the analysis. The chapter on linear models, specifically where he designs the matrices and dummy variables was a bit confusing. That was the only issue I had with the book.



5. This book seems like an excellent reference if you read though it in order and follow along using the example dataset provided online. However, I find that the transition to using my own data is far from clear. The book does not prepare you very well for using your own data, and barely discusses any type of matrices. This book if for univariate analysis, and univariate data.
   As a reference it is definitely not as well suited. Looking up a topic in the index and jumping to that page often drops you in the middle of an example and you have to go back to the beginning of the at least the chapter to understand what's going on.
   Basically after using this book I have found that though I can parrot the examples on the page, I do not understand the reasoning behind the code. Therefore when I go on to try and use my own data, I do not have the understanding and vocabulary necessary to adjust the commands to the needs of my dataset. For example there is a section on graphics (chapter 3) but I was not able to use it to help me figure out how to label a simple chart, unless it was the same chart that was used in the example.

5 comments about An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/Crc Mathematical and Computational Biology).

1. A superb intro to the field. The math is moderate and helpful. Network concepts and their ties to examples and theory are clearly and succinctly presented. This is a textbook but reads easily like a book. Covers key elements while connecting them by at least mention to up-to-date further research. The basics and the grandeur of systems biology. I am trying to remember now anything on the negative side and cannot.



2. The history of science over the past few centuries is to become ever more specialized. The physicists, becomming ever more concerned with the very large (stars, galaxies, the cosmos) or the very tiny (first atoms, then atomic components, now sub-components. The biologists on the other hand were studying much larger things, such as the cells that make up life. Both sciences developed techniques to facilitate their study.
   
   In recent years, researchers have discovered that sometimes these specialized techniques can be used to develop greater insight into what is happening in other sciences.
   
   In this book, Dr. Alon uses his training in physics to examine certain aspects of biology and to use the terminology and mathematics to describe the way these biological networks work.
   
   The goal of the book is to begin the formulation of general laws that apply to biological networks. This is done by providing a mathematical framework in which some of the design principles of biological systems can help to understand biological networks. In looking at the results, an underlying simplicity not seen before appears in biological systems.



3. I'm a Ph.D. student in biophysics. This is the best treatment of systems biology that I've encountered. It treats both the math and the biology with clarity, rigor, and respect. It simplifies without dumbing down. It's beautifully written. If you doubt that systems biology is a real scientific discipline, this book will change your mind.



4. I am a macromolecular crystallographer interested in theoretical systems biology, and this book is a real goldmine. It explains all the concepts behind biochemical systems and networks in a clear, lucid language. This book is a pleasure to read, for both biologists and mathematicians alike.



5. This is a great book for learning about how biology works. I've been wanting to learn a bit more about biology, and I've read many of the popularized science books on the subject. Most serious biology books require a pretty good understanding of organic chemistry. (At first that didn't seem like a problem, after all organic chemistry is just regular chemistry with a bunch of carbon atoms lying around, but the jargon gets so dense that you lose track of what's going on.) This book offers an entirely different perspective on biology that is much more accessible to someone with a general interest in science.
   
   This book looks at biology from the perspective of how genes and proteins interact at a network level, rather than a chemical level. It's a lot like learning electronics -- you can understand a lot about a transistor without knowing how semiconductors work. After explaining the operation of some of the most common network "motifs" the author talks about why those motifs were favored by evolution, in particular what makes them robust and how can they act to minimize errors. The book leaves you with the very interesting question of what characteristics might be different between an engineered system and an evolved one?
   
   The language of the book is very clear, this is a technical book you could easily read for fun. The math is simple, just a little calculus, and if you don't care about the math you can just look at the diagrams.

5 comments about Innumeracy: Mathematical Illiteracy and Its Consequences.

1. I felt like I knew about numbers before the book, and now I realize that I need to review and study numbers! I asked a bunch of friends about some of the simple problems in the book and found that many of them could not figure it out! Definitely read this



2. I have read several "mathematics for a popular audience" books as a high school math teacher who has done graduate work in mathematics. This is considered a classic, but I felt like it was no longer up to date at times. Also, I had the feeling I had read many of the better examples and such in other places - again this book is now a classic. It is good, but I have read similar books that I enjoyed more.



3. "Innumeracy" goes beyond the expectation of a non-mathematician, user-friendly book. It wakes up your awareness of what passes as "statistics", "experts", "economics", and various numeric analysis in the popular media.
   
   I bought the book after seeing it referenced in another science book. I was interested in a basis for how much bias, or straight ignorance, was posing in the guise of expert. I was more than satisfied with "Innumeracy" in this regard.
   
   Read it twice. Put it down for a month, pay attention to what's in the news, etc. then read it again. You will be a much better consumer of numbers.



4. This was an interesting book that I would highly recommend to anyone NOT number-savvy. I had heard good things about it, and as someone who appreciates the importance of math, I thought it would be great to check out. It was written with the lay-person as its target audience, so being someone who already knows a great deal of mathematics, I was underwhelmed. The book is clearly written, and explains concepts slowly and carefully as it illustrates every-day math for the common person.
   
   Honestly, this book felt a bit like "See Spot Run," but for mathematics instead of the English language. Even though it was a bit boring for the mathematically inclined, I highly recommend it for anyone suffering from "Mathematical Illiteracy." If you have ever said to yourself "I'm not a numbers person," then this book is for you.



5. We live in a society that is more and more advanced technologically. Curiously, however, at the same time the nation's math skills are weakening decade by decade.
   
   John Allen Paulos's "Innumeracy" attempts to address one aspect of this situation by offering some rudiments of probability theory. Many times in the lives of individuals and of nations, poor decisions are made due to an inadequate knowledge of probability. Some of the topics the author mentions include regression to the mean, coincidence, correlation and causation, and trade-offs between societal and individual rights. The author also discusses innumeracy as it relates to ESP and UFOs.
   
   Knowing the basics of probability can even help your health. By focusing on the actual probability of your worries coming to pass, you can eliminate many groundless worries from your life and thus save wear and tear on your nervous system.

5 comments about How to Ace Calculus: The Streetwise Guide (How to Ace).

1. ...given the mostly glowing reviews. Don't expect miracles from this guide. Nothing particularly enlightening in its contents, if you had stayed awake during classes....



2. I teach Calculus at the high school level and was very impressed with this book. I recommend it for my students as a supplement. It explains the concepts in "real words" and helps some of them understand. Also, additional examples that are well explained.



3. This book really makes me want to learn Calculus 2.After reading it, I find myself going back to my Calculus textbook for a deeper understanding. The explanations are very clear, humorous and to the point. I even ordered their "How to ace the rest of Calculus". I like the way they explain the derivative as being the slope of the tangent line. I enjoyed that book and I recommend it to anyone who may still hesitate to take a Calculus class.. Bravo!



4. This is horrible it doesn't explain the answers in a step by step process. It is good for summaries of chapters in a high school or college level calculus book .



5. This book was amazing. After failing calculus, I decided I needed some extra help other than just the assigned book. I tried the "Calculus for Dummies" book, as well as this (a friend loaned it to me), and this book was by far the biggest help. If you're having trouble with calculus, or are planning to take calculus, try to find this book.
   
   This book puts forth great information in an amusing manner that doesn't detract from the material (in my opinion, others may vary). Some of the jokes actually helped me with understanding the problem when my teacher's examples didn't help. There were a couple of nights before a big test when I would read this book to cram and actually came away having learned more than in class (given, I'm not the best in class student, especially when it comes to math).

3 comments about Statistics in a Nutshell: A Desktop Quick Reference (In a Nutshell (O'Reilly)).

1. This book is probably not what you're expecting since most O'Reilly Nutshell books assume you already have thorough knowledge of a subject and you are just looking for "cues" in case you forget something. This book is more of a "Head First" type of book in that it assumes no prior knowledge of the subject. Since O'Reilly is planning a Head First book on Statistics, I'd like to see the difference between this book and that one.
   
   This book focuses on using and understanding statistics in a research or applications context, not as a discrete set of mathematical techniques but as part of the process of reasoning with numbers. It integrates the discussion of issues such as measurement and data management into an introductory statistics text. It serves as an introductory statistics book that is compact, inexpensive, and easy for beginners to understand without being condescending or overly simplistic.
   
   The audience for this book includes students taking introductory statistics classes in high schools, colleges, and universities, professionals who need to learn statistics as part of their current jobs, and finally people who are interested in learning about statistics out of intellectual curiosity.
   
   The book focuses on statistical reasoning. In particular, the book focuses on thinking about data, and using statistics to aid in that process.
   
   The book is organized into four parts: introductory material (Chapters 1-6) that lays the necessary foundation for the chapters that follow; elementary inferential statistical techniques (Chapters 7-11); more advanced techniques (Chapters 12-16); and specialized techniques (Chapters 17-19). The following is the detailed table of contents:
   
   Chapter 1, Basic Concepts of Measurement - Discusses foundational issues for statistics, including levels of measurement, operationalization, proxy measurement, random and systematic error, measures of agreement, and types of bias. Statistics demonstrated include percent agreement and kappa.
   
   Chapter 2, Probability - Introduces the basic vocabulary and laws of probability, including trials, events, independence, mutual exclusivity, the addition and multiplication laws, and conditional probability. Procedures demonstrated include calculation of basic probabilities, permutations and combinations, and Bayes's theorem.
   
   Chapter 3, Data Management - Discusses practical issues in data management, including procedures to troubleshoot an existing file, methods for storing data electronically, data types, and missing data.
   
   Chapter 4, Descriptive Statistics and Graphics - Explains the differences between descriptive and inferential statistics and between populations and samples, and introduces common measures of central tendency and variability and frequently used graphs and charts. Statistics demonstrated include mean, median, mode, range, interquartile range, variance, and standard deviation. Graphical methods demonstrated include frequency tables, bar charts, pie charts, Pareto charts, stem and leaf plots, boxplots, histograms, scatterplots, and line graphs.
   
   Chapter 5, Research Design - Discusses observational and experimental studies, common elements of good research designs, the steps involved in data collection, types of validity, and methods to limit or eliminate the influence of bias.
   
   Chapter 6, Critiquing Statistics Presented by Others - Offers guidelines for reviewing the use of statistics, including a checklist of questions to ask of any statistical presentation and examples of when legitimate statistical procedures may be manipulated to appear to support questionable conclusions.
   
   Chapter 7, Inferential Statistics - Introduces the basic concepts of inferential statistics, including probability distributions, independent and dependent variables and the different names under which they are known, common sampling designs, the central limit theorem, hypothesis testing, Type I and Type II error, confidence intervals and p-values, and data transformation. Procedures demonstrated include converting raw scores to Z-scores, calculation of binomial probabilities, and the square-root and log data transformations.
   
   Chapter 8, The t-Test - Discusses the t-distribution, the different types of t-tests, and the influence of effect size on power in t-tests. Statistics demonstrated include the one-sample t-test, the two independent samples t-test, the two repeated measures t-test, and the unequal variance t-test.
   
   Chapter 9, The Correlation Coefficient - Introduces the concept of association with graphics displaying different strengths of association between two variables, and discusses common statistics used to measure association. Statistics demonstrated include Pearson's product-moment correlation, the t-test for statistical significance of Pearson's correlation, the coefficient of determination, Spearman's rank-order coefficient, the point-biserial coefficient, and phi.
   
   Chapter 10, Categorical Data - Reviews the concepts of categorical and interval data, including the Likert scale, and introduces the R x C table. Statistics demonstrated include the chi-squared tests for independence, equality of proportions, and goodness of fit, Fisher's exact test, McNemar's test, gamma, Kendall's tau-a, tau-b, and tau-c, and Somers's d.
   
   Chapter 11, Nonparametric Statistics - Discusses when to use nonparametric rather than parametric statistics, and presents nonparametric statistics for between-subjects and within-subjects designs. Statistics demonstrated include the Wilcoxon Rank Sum and Mann-Whitney U tests, the median test, the Kruskal-Wallis H test, the Wilcoxon matched pairs signed rank test, and the Friedman test.
   
   Chapter 12, Introduction to the General Linear Model - Introduces linear regression and ANOVA through the concept of the General Linear Model, and discusses assumptions made when using these designs. Statistical procedures demonstrated include simple (bivariate) regression, one-way ANOVA, and post-hoc testing.
   
   Chapter 13, Extensions of Analysis of Variance - Discusses more complex ANOVA designs. Statistical procedures demonstrated include two-way and three-way ANOVA, MANOVA, ANCOVA, repeated measures ANOVA, and mixed designs.
   
   Chapter 14, Multiple Linear Regression - Extends the ideas introduced in Chapter 12 to models with multiple predictors. Topics covered include relationships among predictor variables, standardized coefficients, dummy variables, methods of model building, and violations of assumptions of linear regression, including nonlinearity, autocorrelation, and heteroscedasticity.
   
   Chapter 15, Other Types of Regression - Extends the technique of regression to data with binary outcomes and nonlinear models, and discusses the problem of overfitting a model.
   
   Chapter 16, Other Statistical Techniques - Demonstrates several advanced statistical procedures, including factor analysis, cluster analysis, discriminant function analysis, and multidimensional scaling, including discussion of the types of problems for which each technique may be useful.
   
   Chapter 17, Business and Quality Improvement Statistics - Demonstrates statistical procedures commonly used in business and quality improvement contexts. Analytical and statistical procedures covered include construction and use of simple and composite indexes, time series, the minimax, maximax, and maximin decision criteria, decision making under risk, decision trees, and control charts.
   
   Chapter 18, Medical and Epidemiological Statistics - Introduces concepts and demonstrates statistical procedures particularly relevant to medicine and epidemiology. Concepts and statistics covered include the definition and use of ratios, proportions, and rates, measures of prevalence and incidence, crude and standardized rates, direct and indirect standardization, measures of risk, confounding, the simple and Mantel-Haenszel odds ratio, and precision, power, and sample size calculations.
   
   Chapter 19, Educational and Psychological Statistics - Introduces concepts and statistical procedures commonly used in the fields of education and psychology. Concepts and procedures demonstrated include percentiles, standardized scores, methods of test construction, the true score model of classical test theory, reliability of a composite test, measures of internal consistency including coefficient alpha, and procedures for item analysis. An overview of item response theory is also provided.
   
   Two appendixes cover topics that are a necessary background to the material covered in the main text, and a third provides references to supplemental reading.



2. A stunning display of relevant and directed statistical information bound in a concise quick reference guide, suitable for the learned individual.
   
   This book deliver's a user-friendly manual of beginner, intermediary and some advanced methods of analysis within statistics. Though the reader does not need to have a background in statistics, it would suit someone with an interest in statistics and the mathematical principles behind such methodologies. This book offers much more than your basic run of the mill statistical guide as it probes further into the mathematical models that such statistics are based upon. This gives the reader the opportunity to extend the breadth and application of their understanding.
   
   This book is useful in design with topics and chapters clearly identifiable by quick reference tabs. The organisation of the material within is cummulative and very easy to navigate through.
   
   A perfect manual for anyone undertaking further studies be it at a tertiary level or within their occupation. Hands down one of the more aptly constructed and useable reference guides in statistics that I've seen for years. Two thumbs up.



3. A very easy to read and understand book with plenty of really relevant examples. Best chapter is the one that explains the basics that we did back in school and have forgotten.
   Clear examples that are easy to follow. Written for the non mathematical type of person.
   Covers everything I needed for my project. Best statistics book I have used.
   Statistics in a Nutshell: A Desktop Quick Reference (In a Nutshell (O'Reilly))

5 comments about Partial Differential Equations for Scientists and Engineers (Dover Books on Advanced Mathematics).

1. Good book to gain an understanding of the basics involved in PDE's. Could use more worked through examples as applied to practical problems.



2. This is a series of lectures that introduce partial differential equations for engineers and scientists. It is written clearly and carefully, using approachable language to build a conceptual understanding of the phsyical phenomena that inspire the mathematical approach.
   
   This probably won't satisfy people interested in applied mathematics, but engineers should find this a sensible approach. I'd suggest that this could be read alongside an advanced mathematics textbook and will aid the understanding, application and solving of many vital applied physics problems.



3. I teach BVPs at the undergraduate level and I use this text for classroom examples. It presents classical methods for solution of BVPs. Mathematics is provided at the application level so this not a reference for someone interested in the mathematics of PDEs. It does provide references (dated) that I have found useful for additional material. Most are inexpensive so you can add them to your library. Will DOVER consent to placing all of its texts in KINDLE format?



4. I'm a Mechanical Engineer and I wanted to deeper understand some aspects related to differential equations.
   Sometimes, when one finishes University, he knows many concepts about mathematical topics, but without having a clear idea about their real meaning and their different ways to be used. Every time, if one does not have a strong knowledge about Mathematic tools, he cannot apply and completely exploit their power.
   This book is surely helpfull in clarifying many things related to Differential Partial Equations, which are one of the most usefull tool in modern Engineering, nowadays.
   The method of this book (divided in several chapters which represent a single lesson each)is clear and not boring to read (as many Mathematic books are).
   I would suggest this book to people who want to clarify the real meaning of PDEs.



5. This is a great book from mine kind of perspective. Reason why I gave 4 stars is that i haven't finished reading this book so i don't know how good is the rest of the book explained.
   The book explain very simply the basic things regarding pde which is good for someone who isn't mathematician.
   I would definitely recommend this book to engineers and undergraduate students of mathematics.
   Best regards