Book Description
This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.
Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.
The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.
The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).
From the reviews:
"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered."
Journal of Biopharmaceutical Statistics, 2005
"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book"
Technometrics, February 2006
"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally."
Journal of the American Statistical Association, March 2006
Customer Reviews:
very good book, compact but comprehensive.......2007-05-12
This book covers a wide range of topics in Biostatistics, in a comprehensive, but not overwhelming way. In my opinion this book has the potential of being useful to a broad audience, from Statisticians to other professionals who do health related research.
Excellent book ..........2007-01-09
A very specific book, with a lot of details for a statistitian
Book Description
Statistics for the Life Sciences presents the key concepts of statistics as applied to the life sciences, while incorporating tools and themes of modern data analysis. The book emphasizes interpretation of results using real data, which facilitates an understanding of statistics and data through the use of graphical data and analysis.
The Third Edition has added many new sections to cover probability rules, random variables, the Wilcoxon Signed-Rank Test, and two-way ANOVA and ANOVA for randomized blocks designs. In addition, there is expanded treatment of logistic regression in Chapter 12.
This book is an essential statistics reference for professionals and scientists in biology, agronomy, medical and health sciences, nutrition, pharmacy, animal science, physical education, forestry, and other life sciences.
Customer Reviews:
Disappointed.......2007-05-05
I am personally disappointed with this book for the following reasons:
1) Most math books have the answers in the back for nearly all of the odd programs; this book does not. In fact, there's little rhyme or reason for the answers listed in the back. In short, most odd problem answers are not listed yet some of the even answers are given. Go figure..
2) I don't care for the chapter and section layouts. In my calculus text, everything is more developed. In some of the better texts, definitions are given before the explanations are given, which in turn precedes the examples given. This book does not of that. There is not a comprehensive list of definitions at the end of the chapter, the in-chapter definitions are weak, and they fail to fully develop the material before jumping into examples, etc.
But, it is a textbook and it costs > $100, so by publisher standards, it is a home run.
definitely oversimplified........2006-12-28
I took an AP statistics course in high school that went into much better detail than this book ever did. With this book I could not have made it out with the understanding I currently have of statistics without having taken that class years ago. Our instructor was pretty much incompetent, so it was a true test of how well the textbook got the job done. I watched my classmates really struggle with this book. The problem is that the concepts of different test statistics and what they actually mean are too oversimplified. The book does a great job of teaching how through an extensive amount of examples, but not why, and not enough instances or explanations of what should be done when problems deviate from the given example. It is really important in statistics to know how to handle different kinds of data and which tests to apply to them, but the book in my opinion did a poor job of distinguishing and explaining the different types of tests, as well as how the results should be analyzed. I would definitely recommend looking elsewhere for a good statistics textbook. When it comes to mathematics, theory (knowing why a problem is solved the way it is and why it works) is just as important as being able to correctly solve the problem.
Book better than class........2006-12-20
This textbook was required for my statistics class at the University of Wisconsin. I found the book easier to follow with better examples than my lecture was. Often I cannot learn anything right from the book, but this book made it easy with complete examples and simple descriptions of variables and theory. The book was so good, in fact, I rarely made it to class because I learned it better from the book!
Oversimplified.......2006-09-07
The book is reasonably good at explaining simple concepts.
However, the lack of detail does not allow for real life application in a biological field: the concepts are oversimplified and the examples given do not reflect the difficulty of actual basic statistics work in the life sciences.
If you want to buy this book, the questions you should ask yourself are:
1. Are you buying this book just to pass a basic statistics course?
2. Are you buying this book to expand your point of view and understanding of real life applications?
An excellent textbook that teaches by example.......2003-04-17
In a word - wow. This is an outstanding textbook for undergraduate biology students. The number of practical, real life examples exceeds anything else I have seen in a statistics book, permitting the student to follow theory immediately with concrete practice. Examples are drawn from all axes of biology as well - physiology, biogeochemistry, pharmacology, microbiology, animal behaviour and more. I have been disappointed with previous textbooks which fall down in the following ways: 1) too much emphasis on the mathematics of calculation, or 2) lack of practical introductory treatment of moderately advanced topics which are nonetheless necessary to practitioners. This book for me strikes a very good balance between understanding the underpinnings without getting lost in equations, and getting your hands dirty with data in order to learn by example. Coverage is as wide as necessary today: introduction to logistic regression, and a clear treatment of interaction in two-way ANOVA. I do note that multiple regression is not touched. The sole drawback: sticker shock. It will be difficult for students to pay for a book that costs about $100 US. But at least you get what you pay for in this case.
Average customer rating:
- Not for beginners
- More useful than other beginner's texts but...
- The mediumýs viewpoint
- The beginner's viewpoint
- A Great Desk Reference for Biologists
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Biostatistical Analysis (4th Edition)
Jerrold H. Zar
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ASIN: 013081542X |
Book Description
The latest edition of this best-selling biostatistics book is both comprehensive and easy to read.
It provides a broad and practical overview of the statistical analysis methods used by researchers to collect, summarize, analyze, and draw conclusions from biological research data. The Fourth Edition can serve as either an introduction to the discipline for beginning students or a comprehensive procedural reference for today's practitioners.
Customer Reviews:
Not for beginners.......2007-03-16
I own this book, which I purchased for a graduate-level statistics class. This book does include virtually everything you'd need as a biological statistician, but I have found most of it totally unaccessible. It's far too verbose which makes it difficult to plow through and I feel it's mostly obsolete since it makes no reference to computer software. Since statistics is now a field based almost exclusively on computer programs, a book based entirely on doing statistics by hand is not helpful! I'd say, save your $100 and look elsewhere (like the literature and an SPSS manual).
More useful than other beginner's texts but..........2006-07-17
As someone who recently retired from analyzing ecological data after a decade of it, I found this book to be pretty good one-stop shopping. I wouldn't say it's an introduction to stats so much as it is a systematic compilation of all the "traditional" statistical topics (t-tests, regressions, etc). As such, it contained some useful formulas that do not occur in regular "Stats 101" texts, such as sample size estimators for various analyses.
However, there are two things it is missing. As mentioned by other reviewers, there's no coverage (in the edition I have, anyway) of iterative techniques like bootstrapping, Monte Carlo approaches, etc. Those are coming up a lot in everyday statistical work these days.
More important is something missing from nearly EVERY beginning statistics text (and, often, from college education), which is the place of statistical testing in scientific logic. Too many beginners with statistics get stuck on fishing for significant differences in a stale old dataset rather than really thinking about their subject matter. In the absence of context, statistical "significance" can be deceptive and meaningless. One place to start on this subject is with Murphy & Myor's really good book called Statistical Power Analysis. I learned a ton from that book, which is a good companion for nearly any regular stats text. Happy crunching..
The mediumýs viewpoint.......2004-07-22
I had been teacher of Statistic by several years in some universities of Mexico and the Zar book had been a common company in my classroom all the years. Certainly it is not to begginers, but it is very usefull to proffesors. It usually have answer to assess uncommon series data, as non-normal data, or missing data. The book work almost all the time with data series that have normal distributions, and use non-parametric statistical tools to work with other series distributions. There are other books that deal with it best, considering, by example, tests to data with Poisson or binomial distributions (the common in the biological sciences). However, to undergraduate students, and some graduate students, the Zar "normal" approach work fine. Graduate research or doctoral research is done better not with other book in hand but with other statistical approach in mind, and unfortunately there is not only book to do it. Well, in that case, the Zar book help to understand some of the main points to make high statistical analysis.
The beginner's viewpoint.......2004-06-03
Frankly, I am aghast that the publisher calls this book accessible and appropriate for beginners. I purchased it as the required text for an introductory biometry class, and it has contributed very little to my understanding of biostatistical analysis. After chapter 7 (at best), it is simply incomprehensible. The mathematical notation requires far more than a high school algebra background, and the wording is extremely terse. Yes, it does offer real-world examples, and yes, it does offer a large range of statistical tables, and I am sure that it is good reference for people who are already working as statisticians and who have advanced degrees in statistics. However, it is misleading to call Zar a good introductory text - it is completely inappropriate for beginners. It is too concise in a situation where more words would be useful. Sokal and Rohlf 2nd ed. is far better; Fowler et al. also proved helpful.
A Great Desk Reference for Biologists.......2004-02-10
I have found this book more approachable and user friendly than Sokal and Rohlf. Zar is an excellent desk reference, and has solved a number of statistical problems for me. I reccomend it to anybody who regularly uses statistics in a biological context.
Average customer rating:
- Complicated language
- Principles of Biostatistics
- Hope this suggestion helps u decide
- Biostatistics simplified
- Great book - one of few!
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Principles of Biostatistics (with CD-ROM)
Marcello Pagano , and
Kimberlee Gauvreau
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Principles of Biostatistics Student Solutions Manual
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ASIN: 0534229026 |
Book Description
Marcello Pagano and Kimberlee Gauvreau's PRINCIPLES OF BIOSTATISTICS, Second Edition is a concepts-based introduction to statistical procedures that prepares public health, medical, and life sciences students to conduct and evaluate research. With an engaging writing style and helpful graphics, the emphasis is on concepts over formulas or rote memorization. Throughout the book, the authors use practical, interesting examples with real data to bring the material to life.
Customer Reviews:
Complicated language .......2007-09-29
The language in this book is very hard to understand. I took statistics when I was an undergrad and but this book is so hard to understand. The authors tried to show more steps in the math examples maybe try to make it easier for the reader but it just make it MUCH more complicated to follow. Sometimes I have to read my undergrad statistics book in order for me to understand the same thing it says in this book.
Principles of Biostatistics.......2007-09-19
This book does not give step-by-step instructions on how to solve problems. Therefore, I feel it is not a good book. I still feel very lost after reading chapters in this book.
Hope this suggestion helps u decide.......2007-09-09
This is my first time that I purchased online. I got the book within 3 days and it's in a good condition. Cheaper, got a book, and on time...isn't it enough?
Biostatistics simplified.......2007-06-27
Much easier to grasp than another text on the subject that I have experienced, (Biostatistics... A foundation for anlaysis in the Health Sciences; 8th Edition. Wayne W. Daniel). I am an MPH student with limited math background. Had a 4.0 going before my first experience with biostats. A "D" won't cut it in the program I am completing. Found an alternative Biostats course and the required text,(Principles of Biostats;Marcello Pagano), is much, much, easier for me to grasp. The real world examples and simplified methods make for an easier comprehension for those of us who lack a strong mathematic prerequisite.
Great book - one of few!.......2007-03-23
I've read the other reviews, and seems either you love it or hate it. I used this at Harvard School of Public Health on my 3rd time through bio-statistics (college, med school, MPH). Only this time I got it right, and think it was the balance between some non-calculus theory and practical examples in this book. Not understanding probability distributions at all leads to misapplication, and misuse. I have frequently turned to this as "tune-up book" if I've been away too long. The exercised sets are helpful and "realistic"; however, I do understand the problem with text-books and teacher's manuals that give only 1/2 the answers.
Book Description
This classic text takes an applied and computer-oriented approach to its topical coverage. The book is intended for one or two semester courses in biostatistics at the undergraduate or graduate level offered by departments of biostatistics, statistics, mathematics, nursing and other allied health disciplines, and is also used in some departments of forestry and animal husbandry. Nearly all the examples and exercises make use of real data from actual research projects and reports from health sciences literature. Where appropriate, Minitab, SPSS and SAS commands and printouts are included as part of the examples and solutions to exercises.
Customer Reviews:
Helpful but technical.......2006-11-10
This book is extreamly helpful for academic research. It can be somewhat more technical than most people would need.
Not as impressive as I first thought.......2005-09-23
Daniel obviously knows his statistics; but, I wouldnt think that is too helpful for individuals reading or studying from his textbook.
The reasons are numerous, and all these reasons would reduce anyone's chances of solely using this book, or even using it at all.
The textbook is well organized, however Daniel's writing often is pedantic, repetitive (not in the helpful way) and ambiguous at best.
The examples and solutions occassionaly have serious errors in them which affect the overall outcome of the test (A second consideration is that the book is in it's 8th edition!!! therefore such errors are unacceptable for a person such as myself).
An example can be found on page 239 (example 7.3.2). The pooled variance, as calculated by Daniel is approximately off by 100 simply because he didnt give attention to dividing the numerator with the proper pooled D.F of the samples. The chapter ironically was on hypothesis tests, something extremely important to any line of empirically oriented statistics.
In Chapter 8; which is probably the most important chapter in Bistatistics (ANOVAs) he does not mention the relationship between MSW and sample SD. Also, his usage of Summation in formulas often are unnecessarily overcomplicated. Such is not even seen in professional journals.
I did like this textbook regardless of its many shortcomings, its not because I liked the author's style of writing. Its more or less the fact that my lecturer (I assume) used this book heavily in his lectures and so I used it as a supplementary text.
I would suggest, Chap T. Le's Introductory Biostatistics. However he goes too much into nonparametric methods and proportions and doesnt cocentration (to the degree I wanted) on continous data.
More robust and probably cost effect books are :Introductory Statistics for the Life Sciences by Samuels. But the Best book I have ever seen on the subject is "Introductory Biostatistics for the health sciences" By Chernick and Friis. The book is well priced and no portion of this book, I have seen as being useless.
Excellent Text for 2nd Statistics Class.......2004-10-25
I'm taking my first biostatistics class in medical school, but the text I am using in class (Rosner) has lost me. I subsequently borrowed Daniel's book from the library (only because it has 7th editions), and I am glad that I picked it! Daniel is a good writer. The book is well organized and laid out. Important concepts are emphased and explained with minimum mathematics involved. The well thought out examples are worth working through as well for clarification of the applications of important concepts. However, as a beginner in statistics, I was lost in the midst of mathematics on certain concepts (given that I have a relatively strong mathematics background) without really understanding the meaning of some very basic terms, like percentile, confidence intervals.
What I do is to read another reference book that explains the very basic concepts in plain English first before reading this text. I am currently using Munro's Statistical Methods for Health Care Research. While both of them cover the same set of concepts, Daniel gives me the mathematical and more advanced explainations compare to Munro.
Very Good.......2003-12-19
I have used this and other texts by Daniel over the years and I find you can not go wrong with his works. He is a no nonsense author and a very good writer who uses plenty of examples. Get his nonparametric book also.
Solid introductory reference.......2003-01-09
The title is very appropriate - this text provides a solid foundation in biostats. I used it for an intro course in grad school, and working through the text was very worthwhile. Previously cloudy concepts are now more clear, and I have a great reference for future use. More in-depth biostats deserves a consultation with a statistician, not a longer text. I agree with other reviewers that there are occasional mistakes (which need to be fixed - this is not even the first edition), but overall I would still highly recommend it.
Average customer rating:
- THE Biometry textbook of choice
- The Standard Introductory Textbook on Biostatistics
- Very good book
- My Bible
- Excellent self-tutorial
|
Biometry
Robert R. Sokal , and
F. James Rohlf
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ASIN: 0716724111 |
Customer Reviews:
THE Biometry textbook of choice.......2007-08-20
I use this as a personal reference. Have examined many dozens of statistics books and this is the Bible, as far as I am concerned. It is clear, has excellent coverage, and is actually written engagingly! If you are going to have only one statistics book--it should be this one.
The Standard Introductory Textbook on Biostatistics.......2007-05-07
"Biometry" should be regarded - if it isn't already - as the standard practical guide to both parametric and nonparametric univariate biostatistics. Although it is aimed primarily for researchers and students in the biological sciences and medicine, there are ample practical examples which should be useful to those in psychology, sociology and other fields where knowledge of statistics and statistical methods is quite essential. I own a copy of the second edition, which I've had for more than two decades, regarding it as my "go-to" book if I have questions about various univariate statistical techniques. As another reviewer has noted, this book is especially strong in discussing nonparametric statistics. I might add too that it is quite good in discussing tests of significance related to Analysis of Variance (ANOVA) and simple linear regression. Much to their credit, the authors have written a superb text in clear, often concise, English that could be used as a self-teaching introductory guide for a practical understanding of univariate biostatistics. However, I will note that those interested in learning the theoretical foundations of the parametric and nonparametric univariate biostatistics covered in "Biometry" should consult another book which does emphasis these topics: Zarr's "Biostatistical Analysis", which I agree is a superb introductory text on theoretical biostatistics.
Very good book.......2006-11-04
The product is in very good condition. The cover was without any damage as was the inner.
My Bible.......2006-10-10
I used this book in grad school as my textbook and constantly use it now in my job as a six sigma black belt.
Examples are excellent.
Excellent self-tutorial.......2002-10-04
The book is based upon biostatistics courses taught by the authors. It is designed to be used as a self-tutorial if so desired. The explainations and examples are excellent.
Book Description
Biomedical and social science researchers who want to analyze survival data with the SAS System will find just what they need with this easy-to-read and comprehensive guide. Written for the person with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book ensuring that even the uninitiated becomes a sophisticated user of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered such as time-dependent covariates, competing risks, and repeated events.
Supports releases 6.09 and higher of SAS software.
Customer Reviews:
Nice reference for survival analysis.......2007-01-11
So far, this book has been a useful reference for survival analysis. It is clearly written and the xplanatins are understandable and helpful. It would be nice to have a newer edition that addresses changes in later versions of SAS.
Learn By Doing.......2005-06-14
If you have data that fit the general category "time to event," and are not suitably analyzed by repeated measures ANOVA, you are probably looking at doing a survival analysis (also known by several other names). If you are working largely on your own, and you learn best by doing, you cannot--as far as I know--do better than Allison's book. Of course it all but locks you into using SAS for analyses, but his explanations of proportional hazards and other models are the best I've found among a dozen textbooks and stats package manuals (some of which made sense only after reading Allison). What makes this book so good is that it will have you running your analyses in just hours. The examples are superb take-off points. I was not a SAS user before reading the book and therefore took a little extra time to figure out dataset manipulations and such in SAS, but that was minor effort compared to the rewards of having Allison's clearly written book as a guide. The price of this book represents only a fraction of its value.
Extraordinarily Clear and Useful.......2000-02-06
I've used a number of this author's books and they all share in common lucidity, utility, and rigor. This book makes it easy to grasp complex ideas, provides comprehensible examples, gives sample SAS code so that implementing the methods is as straightforward as possible. Plus, it is clear that the author is a subtle and first-rate methodologist, who innovates in this area as well as teaches it.
Best how-to book on survival analysis using SAS. Very useful.......1999-06-22
This book is well-written, well-organized, and very practical. I found it invaluable in conducting my research. My only recommendation for the author for his next edition is to include a chapter on dealing with correlated event times, like time-to-promotion and time-to-quiting in his policemen example (pg 249).
Book Description
- Includes a new chapter on logistic regression.
- Discusses the design and analysis of random trials.
- Explores the latest applications of sample size tables.
- Contains a new section on binomial distribution.
Download Description
* Includes a new chapter on logistic regression.
* Discusses the design and analysis of random trials.
* Explores the latest applications of sample size tables.
* Contains a new section on binomial distribution.
Customer Reviews:
Very good book.......2007-03-12
This book is an excellent alternative to Agresti's "Categorical Data Analysis" for the analyzing of categorical data. The book is comprehensive and less mathematically demanding than Agresti. The book does a tremendous amount with contingency tables and epidemiologic types of data and has many good worked out examples.
There are a couple of features that could be improved in the next edition:
1) Give the statistical tests that are presented names.
Often statisitical procedures/tests are given and they are not given an explicit name. I think that this is an intentional practise of the authors, but I found it very confusing. For instance, there are many chi-square tests out there, each of which can be written in different ways. Why not call them "Pearson's chi-square", "Cochrane's chi-square", etc... so that the reader knows what the authors are talking about?
2) Not enough time devoted to the subject of combining simple proportions (i.e. not fourfold tables) from several samples/studies. Only one method is shown when several others exist.
3) ALL the common methods used to transform proportions should be presented and explained. For instance, the arcsine transformation is left for an exercise.
4) The writing was a bit terse and cryptic at times. I wish the authors had opted for a simpler English sentence structure and aimed to write at as low a level as practically possible. This encourages understanding of the topic rather than the development of eloquent prose.
5) The references were good but the way they were cited was not. In line author names is an outdated reference method that bogs down sentences and clutters pages with useless text. Simple numeric citation markers would have been better.
6) Bayesian methods are developed, but not a much as I might otherwise have hoped.
Customer Reviews:
Excellent For USMLE.......2000-10-17
I took my USMLE in 1997, I found this review extremel helpfull, I did not have any problemes answering questions in USMLE, which I owe to the great presentation of Info, easy to remember the well organized materials, tables, figures. Now I am a resident, I easily remember the pages, tabletes. I frequently used before journal clubs. I recomended for every USMLE taker. It worth it, it deserve SIX Stars if possible.
Average customer rating:
- The backwards book for biostatistics
- My Prof had trouble understanding the book!
- Poor layout
- Awesome Biostats Primer!
- Fundamentals of Biostatistics by Rosner
|
Fundamentals of Biostatistics (with CD-ROM)
Bernard Rosner
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Study Guide For Fundamentals Of Biostatistics
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The Little SAS Book: A Primer, Third Edition
ASIN: 0534418201 |
Book Description
FUNDAMENTALS OF BIOSTATISTICS (WITH CD-ROM) leads you through the methods, techniques, and computations necessary for success in the medical field. Every new concept is developed systematically through completely worked out examples from current medical research problems.
Customer Reviews:
The backwards book for biostatistics.......2007-03-23
At the time I was taking bio-statistics for my MPH at Harvard School of Public Health, a friend was taking a different class using this book. I ended up buying it, but only as a reference. Althought the material is all here, the organization is scrambled with theory intermixed with the example that starts the topic discussion - some may like this, but personally it drives me crazy. At the end of the semester, I had a wonderful grasp of statistics, and my friend was pulling his hair out. One real plus of this book is that the index includes the clinical examples that generate the discussion, so I do use this book as a reference for "like-problems".
My Prof had trouble understanding the book!.......2006-12-18
My prof had us buy this book for an intro stats class for grad school. She didn't know how good it would be, but thought it applied to our health policy program. This book was not very good. At one point even our prof said she did not like the book and thought the practice questions were unclear at times. Unless your prof forces you to use this book, I would look at easier books (this is not good for a basic stats class). We also used SAS and this book wasn't any help with that portion of the course. It was not worth the $110 price tag. If you are a prof looking for a stats book, please don't select this one (the price alone is crazy).
Poor layout.......2006-11-10
I was assigned this text for my biostatistics class. Unfortunately, it is a poorly designed textbook, as everything is 'backwards'. Rosner gives examples before he introduces the material; he derives formulas before giving the real equation to use.
The only good thing about the text are the summaries included on the CD-rom. I have decided to read these instead of the actual text, because they are straightforward and leave out extraneous material.
Awesome Biostats Primer!.......2006-02-01
I'm currently an undergraduate student at Univ. South Florida majoring in social work (BSW). I am also doing a math minor because I plan on going on to graduate school in a dual program, social work (MSW) and public health-biostatistics (MSPH).
Having read through the first five chapters (can't put the book down), I found this textbook gives just enough information on the subject matter without going into math theory. Afterall, biostatistics is an applied field not theoretical.
This is a perfect textbook to get primed in the field of biostatistics. I cannot wait to finish this text and learn more theory and history of the many facets that biostatistics has to offer as it relates to the behavioral sciences.
The one drawback about the book is that it does not offer much on how to use a statistical analysis software package, rather it assumes knowledge in this area and just provides the data sets used in the book. A supplimental workbook for this text on the after mentioned topic would be wonderful.
Fundamentals of Biostatistics by Rosner.......2005-11-17
This is an easy-to-read volume on the implementation of statistics for medicinal applications. The author describes the following:
- measures of location i.e. medium white blood counts
- properties of the standard deviation and special case analyses
- graphic methods
- laws of probability
- gynecological problems
- demographic problems and inference
- hypothesis testing and confidence interval analysis
- goodness of fit for regression problems
This work would have a wide audience of readers throughout the
medical world. It is priced reasonably for consumer-conscious
purchasers. The author provides a rendition geared to practitioners. Much of the work is crafted for technical
analysis by professionals , as opposed to theoretical mathematics. For instance, the volume is useful to confirm
medical hypotheses within predefined confidence intervals.
Some reviewers have indicated that the later part of the text
is complicated. For instance, the t-distribution and estimation
techniques may require a simpler explanation. In college, I took
nine reasonably rigorous courses in higher mathematics.
During those courses, I found that the Schaum's Outlines were
good in the areas of calculus, differential equations,
linear algebra, probability and statistical inference. Each
outline provided nearly 1000 solved problems with both theory
and practice explained comprehensively. Students of the Rosner
text would be helped immensely by the Schaum's Outline Series.
This acquisition is still quite good for the price charged.
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