Statistics For People Who (Think They) Hate Statistics

Book Description

This Second Edition of the bestselling text teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. Researchers and students who find themselves uncomfortable with the analysis portion of their work will appreciate this book’s unhurried pace and thorough, friendly presentation.

Salkind takes students through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. In addition, there is coverage of SPSS (and data sets for hands-on experience), and a review of more advanced statistical techniques, such as reliability, validity, introductory non-parametric statistics, and more. Pedagogical features include sidebars offering additional technical information about the topic and set-off points that reinforce major themes. Finally, questions to chapter exercises and a complete glossary are located at the back of the book.

Throughout the book, Salkind offers readers:

Difficulty Rating Index for each chapter’s material for each chapter’s material
Tips for doing and thinking about a statistical technique for doing and thinking about a statistical technique
Top Ten for everything from the best ways to create a graph to the mosteffective techniques for data collection
Tech Talk boxes for readers who want additional details and commentary on statistical procedures
Things to Remember offer readers reviews and reminders of how material presented earlier relates to a technique being presented
Steps that break statistical techniques down into a clear sequence of procedures
SPSS Tips for executing each major statistical technique
Time to Practice exercises at the end of each chapter, followed by complete solutions to each problem
Appendices contain an introduction to SPSS as well as data sets (also available online) used in the completion of chapter exercises and end-of-chapter problems

Praise for the First Edition "I liked its humorous approach, which indeed helps to reduce statistical anxiety. The design of the book is inviting and relaxing, which is a plus. The writing style is great and the presentation is appropriate for my students. A fun and well-written book, it is easy to read and use, and presents statistics in a user-friendly way. . . . I would recommend it for sure."
--Minjuan Wang, San Diego State University

"Salkind’s book is in a class by itself. It is easily the best book of its kind that I have come across. I enthusiastically recommend it for any one interested in the subject, and even (and especially) for those who aren’t!"
--Russ Shafer-Landau , University of Wisconsin

" Statistics for People Who (Think They) Hate Statistics really makes students learn and enjoy statistics and research in general. Students especially like the Ten Commandments and Internet sites."
--Valerie Janesick, Roosevelt University

" Statistics for People Who (Think They) Hate Statistics is definitely the right book for people who have to overcome that familiar anxious feeling when opening a standard statistics book and who having finally managed to do so are still not able to make much sense of it all. The book by Salkind is easy and pleasant to read and one that hardly needs any pre-knowledge of the field to be able to follow the author’s train of thoughts. Salkind has managed to bring statistics home to people who hate statistics, or thought they did."
--STATISTICAL METHODS IN MEDICAL RESEARCH

New to the Second Edition:

Downloadable practice data sets at http://www.soe.ku.edu/faculty/Salkind/stats_fpwhs/
New chapter on factorial analysis of variance
New chapter on reliability and validity
New section on effect size
An entirely revised test bank instructor's manual

Customer Reviews:

Review of Sats Book.......2007-01-19

This book really helped to simplify much of the statistical information that I received in class. I warn that some chapters are more digestible than others but overall it is a good book for someone who is likely to struggle in a statistics class.

Great book!.......2005-08-09

Really helps stats seem easier. Recommend this to anyone who has trouble understanding statistics.

Math Idiot Aces Stats.......2005-03-20

This is the finest book in its class. As a self-described "math idiot" this text made complex equations simple to understand. Step by step method for each and every equation, explaining what everything means and best of all...WHY it is important. Two thumbs up!

Very helpful BUT...........2002-05-01

This book was great at explaining the principles behind the math. However-- THERE WERE HUGE MISTAKES!!! The formula for the correlation coefficient for example, had a misplaced parenthetical that changed the formula. As a rookie in this area I was in tears trying to figure out my homework. This was not the only error, but it certainly was the worst!!!

Otherwise, the examples make it easy to understand the concepts of statistics, and certainly made it so I was able to ace the course. I just wish it hadn't had so many errors.

At last...a book that students can follow!.......2001-05-14

This is an easy to follow, well written book that students find useful. I have used it for teaching undergraduate research and statistics and as a supplement for graduate level research. It is written on a level so that almost all students can follow it and it provides excellent examples.

Average customer rating:

great overview of the topic
up-to-date account of methods for observational studies

Observational Studies
Paul R. Rosenbaum
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 0387989676

Book Description

An Observational study is an empiric investigation of the effects caused by a treatment, policy , or intervention in which it is not possible to assign subjects at random to treatment or control, as would be done in a controlled experiment. Observational studies are common in most fields that study the effects of treatments on people. The second edition of ¿Observational Studies¿ is about 50 percent longer than the first edition, with many new examples and methods. There are new chapters on nonadditive models for treatment effects (Chapter 5) and planning observational studies (Chapter 11) and Chapter 9, on coherence, has been extensively rewritten. Paul R. Rosenbaum is Robert G. Putzel Professor, Department of Statistics, The Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association.

Customer Reviews:

great overview of the topic.......2006-03-18

The book is very well written. It gives a great overview of the fundamental problems of causal inference in observastional studies. It has a lot of examples, homeworks and extensive references in every chapter.

up-to-date account of methods for observational studies.......2002-02-20

Many years ago the famous statistician Ronald Aylmer Fisher criticized analyses that linked lung cancer to smoking. He argued that these studies had hidden biases because they were not controlled experiments. He proposed that smokers could be different from non-smokers because of a genetic propensity to desire cigarettes and that this genetic trait could be correlated with a higher incidence of lung cancer. Thus it would be possible to see a higher frequency of lung cancer among smokers because of this genetic trait rather than because the smoking itself causes the cancer. As far-fetched as this argument may seem to us today, it is based on sound statistical principles and points out some of the potential problems that occur with observational studies.

Although randomized control trials are the best way to determine differences in treatment effects, they are not always practical or ethical. It would be wrong to randomly choose subjects and force some of them to smoke.

Getting around issues of bias in observational studies was first addressed by Cochran who published a book on the subject in 1983. Rosenbaum came out with his own book in 1995 and this second edition expands and updates that popular text.

In Chapter 1 he present examples of observational studies and raises many important issues. Chapter 2 explains the principles of randomized controlled experiments. In Chapter 3 he covers overt bias and some of the basic methods to adjust for it. The sensitivity of observational studies to hidden biases is covered in Chapter 4.

This book is well written, authoritative and contains numerous references and examples. It also includes a chapter on how to plan an observational study.

Book Description

"Provides a comprehensive summary of the continuously growing literature and research activities on the regulatory requirements, scientific and practical issues, and statistical methodology of the design and analysis of bioavailability and bioequivalence studies. Includes several new chapters."

Statistical Methods in Cancer Research: Volume II: The Design and Analysis of Cohort Studies (Iarc Scientific Publication, No 82)

Average customer rating:

Not a good textbook

Statistical Methods in Cancer Research: Volume II: The Design and Analysis of Cohort Studies (Iarc Scientific Publication, No 82)
N. E. Breslow , and N. E. Day
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Paperback

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Case-Control Studies: Design, Conduct, Analysis (Monographs in Epidemiology and Biostatistics)

ASIN: 9283201825

Book Description

This book complements the first volume in the series, on case-control studies, and the two together provide a comprehensive account of the analysis of the major types of study in cancer epidemiology. In addition, this volume has a chapter on study design, covering both the case-control and cohort approach. The scope ranges from an account of the elementary and descriptive approaches to cohort analysis to the fitting of regression models for incidence rates with general risk functions. Particular attention is given to the use of a case-control approach embedded in a cohort study. As in the first volume, all the methods described are illustrated by examples from real studies, and the data from these studies are provided in appendices to enable the reader to go through the computations themselves. The book is intended for the medical epidemiologist with an interest in the quantitative aspects of the subject, and the statistician who is looking for a reasonably complete development of the statistical concepts and methods in current use in this area of epidemiology.

Customer Reviews:

Not a good textbook.......2002-11-11

Breslow and Day's Cancer Research book features poor readability and a presumptious way of writing. Their book seems to be more suitable for those beauracratic agencies or just for decorating your shelves...

Book Description

Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There are a myriad of potential biases to consider, but little guidance about how to asses the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate it successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesized biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.

Network Epidemiology: A Handbook for Survey Design and Data Collection (International Studies in Demography)

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Network Epidemiology: A Handbook for Survey Design and Data Collection (International Studies in Demography)

Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Hardcover

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ASIN: 0199269017

Book Description

Over the past two decades, the epidemic of HIV/AIDS has challenged the public health community to fundamentally rethink the framework for preventing infectious diseases. While much progress has been made on the biomedical front in treatments for HIV infection, prevention still relies on behaviour change. This book documents and explains the remarkable breakthroughs in behavioural research design that have emerged to confront this new challenge: the study of partnership networks. Traditionally, public health research focused on the "knowledge, attitudes, and practices (KAP)" of individuals, an approach designed for understanding health-related behaviour like seat-belt wearing and cigarette smoking. For HIV and other sexually transmitted infections, however, there are at least two people involved in transmission. This may not seem like a big difference, but in fact it changes everything. First, it means that your risk depends on your partners -- and on their partners, and their partners: it depends on your position in the network of partnerships. Consider, for example, the rise of infections among monogamous women. Second, it means that individuals are not free to simply change their behaviour -- condom use, or abstinence, needs to be negotiated with a partner. both the epidemiology of risk and constraints to behaviour are therefore a function of the partnership network. And our ability to design effective prevention strategies depends on our ability to measure and summarize that network. Using the traditional research designs, you would not see this network at all -- you would only see the unconnected nodes. They key to solving this problem lies in Network Analysis, before now a relatively obscure subfield in Sociology. For empirical studies of networks to become feasible, however, many problems had to be solved. This book documents the rapid progress that has been made. It brings together eight pioneering studies that have sought to map the networks that spread infection around the world. Each chapter reviews the questions that drove the study, the changes in methodology that were needed to implement the network survey, the mistakes and successes encountered, and the central findings that the network design made possible. An introduction provides an overview of network survey design, a glossary provides a summary of network terminology, and example questionnaires from each study provide a template for further research. This is a unique and valuable resource for the international public health research community.

The Design and Analysis of Research Studies

Average customer rating:

intermediate level stats book on research studies

The Design and Analysis of Research Studies
Bryan F. J. Manly
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0521425808

Book Description

This book provides students and research workers in the biological, medical and social sciences with the statistical background needed to collect and analyse data in an intelligent and critical manner. Key examples and case studies are used to illustrate commonly encountered research problems and to explain how they may be solved or even avoided altogether. Professor Manly also presents a clear understanding of the opportunities and limitations of different research designs, as well as an introduction to some new methods of analysis that are proving increasingly popular. Topics covered include the differences between observational and experimental studies; the design of sample surveys; multiple regression and its generalizations to log-linear and logistic models; experimental and quasi-experimental designs; interrupted time series; computer intensive methods of statistical inference; and the ethical considerations of research. In the final chapter, there is a useful discussion of how the various components of a research study (including deciding on the objectives, planning, designing, and the collection and analysis of data) come together. This practical and well-structured book will be essential reading for graduate students and researchers in a wide range of disciplines, including biology, anthropology, medicine and the social sciences.

Customer Reviews:

intermediate level stats book on research studies.......2000-08-10

Manly has written a nice intermediate level book on research studies that is particularly useful for statisticians and researchers in the medical field. In addition to being well written and covering many of the common topics like observational versus experimentally designed studies, bias and confounding, survey design and regression, Manly covers topics not common to most texts including: (1) mark-recapture sampling, (2) size-biased sampling, (3)interrupted time series, (4) some advanced designs such as split plots, latin squares, nested factors and repeated measurements, (5) computer-intensive methods, (6) ethical considerations in experiments and (7) a chapter on synthesis which goes through the steps in carrying out a good research study.

Computer-intensive methods covered in Chapter 9 such as permutation and bootstrap methods are covered in more detail in Manly's book "Randomization, Bootstrap and Monte Carlo Methods in Biology." There are also a number of other specialized texts on these topics.

Book Description

This book takes the reader through the entire research process: choosing a question, designing a study, collecting the data, using univariate, bivariate and multivariable analysis, and publishing the results. It does so by using plain language rather than complex derivations and mathematical formulas. It focuses on the nuts and bolts of performing research by asking and answering the most basic questions about doing research studies. Making good use of numerous tables, graphs and tips, this book helps to demystify the process. A generous number of up-to-date examples from the clinical literature give an illustrated and practical account of how to use multivariable analysis.

Customer Reviews:

Good support for clinicians.......2007-01-05

I think It is a good support for clinicians who are intented to know statistical bases before submission of a scientific paper.

Statistical Evaluation of Measurement Errors: Design and Analysis of Reliability Studies

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Statistical Evaluation of Measurement Errors: Design and Analysis of Reliability Studies
Graham Dunn
Manufacturer: A Hodder Arnold Publication
ProductGroup: Book
Binding: Hardcover

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Measures of Interobserver Agreement

ASIN: 0340760702

Book Description

This is a practically oriented introduction to the realiability of measurements. One of the implicit themes is that the measurement models and the statistical methods used in the assessment of accuracy are common to virtually all fields of scientific endeavor. For this latest edition, Dunn has integrated the design and analysis of this type of study to make it easier and included new data sets and examples. Also, he has included the hot new topics of Monte Carlo simulations and the bootstrap, making this an essential guide for all students and scholars of applied statistics.

Longitudinal Data Analysis: Designs, Models and Methods

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Longitudinal Data Analysis: Designs, Models and Methods
Catrien C. J. H. Bijleveld , Leo J Th van der Kamp , Ab Mooijaart , Willem van der Kloot , Rien van der Leeden , and Eeke Van Der Burg
Manufacturer: Sage Publications Ltd
ProductGroup: Book
Binding: Paperback

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ASIN: 0761955380

Book Description

By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes.

However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.

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