Like its two successful previous editions, Health & Numbers: A Problems-Based Introduction to Biostatistics, Third Edition, is the only fully problems-based introduction to biostatistics and offers a concise introduction to basic statistical concepts and reasoning at a level suitable for a broad spectrum of students and professionals in medicine and the allied health fields. This book has always been meant for use by advanced students who have not previously had an introductory biostatistics course - material often presented in a one-semester course - or by busy professionals who need to learn the basics of biostatistics. This user-friendly resource features over 200 real-life examples and real data to discuss and teach fundamental statistical methods. The new edition offers even more exercises than the second edition, and features enhanced Microsoft Excel and SAS samples and examples. Health & Numbers, Third Edition, truly strikes a balance between principles and methods of calculation that is particularly useful for students in medicine and health-related fields who need to know biostatistics.
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"...a revised and expanded edition..." (Journal of the American Statistical Association, December 2002)
--This text refers to an alternate
Paperback
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From the Publisher
User-friendly in its presentation, this concise text avoids dry language and complex formulas which can be intimidating. Illustrates the application of statistics by using examples drawn from published biomedical and epidemiological literature. Provides students with the tools to apply and interpret fundamental statistics by using proportions, rates, continuous measurement, ratios, confidence estimation, probability models and basic hypothesis testing. Self-study questions and exercises at the end of each chapter are also included.
--This text refers to an out of print or unavailable edition of this title.
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8 of 9 people found the following review helpful:
1.0 out of 5 stars
Warning: Text contains many errors,
By minnzo (MN USA) - See all my reviews
This review is from: Health and Numbers: A Problems-Based Introduction to Biostatistics (Paperback)
+ Note: This review was originally written for another book from this author, but touches on my experience with this text as well.
It is mind-boggling how one can have so many mistakes in a textbook like this. This book was required for our Biostatistics II class, and I am really displeased by all of the mistakes. What is the worst offense is that some of the answers for test questions are wrong. For example, the one way ANOVA problem 7.21 has the wrong F-statistic: the wrong answer. Others in the class have complained about this text as well. This is simply amazing to me, and leaves me not trusting much of the text in this book. His other book "Health and Numbers" is just as terrible; the professor that used that book for class made a list of the mistakes they found, and us students in that class found many more along the way. I ran into another statistics book that takes all of the procedures step-by-step and really made it simple for me. This book, and his other are not recommended.
1.0 out of 5 stars
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This review is from: Health and Numbers: A Problems-Based Introduction to Biostatistics (Paperback)
As far as a statistics book goes, this is downright awful. Some concepts are presented in as little as one sentence which should really be expanded upon. This was a required textbook for my graduate level biostats class. After reading some of the chapters and still not being able to complete the problems, I finally gave up and only used it to get the problems I had to do for homework. I used a combination of a different statistics textbook and the internet to complete the problems. Other students in my class complained about this book as well.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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disease status, mean atmospheric smoke, click the paste function icon, log clotting times, tea factory workers, net food supply, state your hypotheses, national smoking rate, name your test, cumulative frequency graph, population odds ratio, preoperative variables, calculate the odds ratio, cases versus controls, cases versus the controls, conditional contribution, confidence estimation, common odds ratio, test size, serum acid phosphatase, few isolated points, hypothesized value Key Phrases - Capitalized Phrases (CAPs): (learn more)
Presentation of Data, New England, Comparison of Population Proportions, Regression Analysis, Comparison of Population Means, Central Limit Theorem, United States, World War, Third Edition, John Wiley, Problems-Based Introduction, Source of Variation, Hypothesis Testing, Nursing Home, New Zealand, New York, Mean Standard Deviation, Deaths Persons Deaths, Subject Before After After-Before Difference, Total Positive, Single Factor, Women Height, Corn Lakes Oak Bran, Data Analysis, Total Category Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
disease status, mean atmospheric smoke, click the paste function icon, log clotting times, tea factory workers, net food supply, state your hypotheses, national smoking rate, name your test, cumulative frequency graph, population odds ratio, preoperative variables, calculate the odds ratio, cases versus controls, cases versus the controls, conditional contribution, confidence estimation, common odds ratio, test size, serum acid phosphatase, few isolated points, hypothesized value Key Phrases - Capitalized Phrases (CAPs): (learn more)
Presentation of Data, New England, Comparison of Population Proportions, Regression Analysis, Comparison of Population Means, Central Limit Theorem, United States, World War, Third Edition, John Wiley, Problems-Based Introduction, Source of Variation, Hypothesis Testing, Nursing Home, New Zealand, New York, Mean Standard Deviation, Deaths Persons Deaths, Subject Before After After-Before Difference, Total Positive, Single Factor, Women Height, Corn Lakes Oak Bran, Data Analysis, Total Category Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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