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E-raamat: Basic Statistics - A Primer for the Biomedical Sciences 4e: A Primer for the Biomedical Sciences 4th Edition [Wiley Online]

(University of California, Los Angeles, CA), (University of California, Los Angeles, CA)
  • Formaat: 272 pages, Charts: 6 B&W, 0 Color; Drawings: 4 B&W, 0 Color; Tables: 0 B&W, 0 Color; Graphs: 39 B&W, 0 Color
  • Ilmumisaeg: 28-Aug-2009
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 047049686X
  • ISBN-13: 9780470496862
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  • Wiley Online
  • Hind: 144,85 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
Basic Statistics - A Primer for the Biomedical Sciences 4e: A Primer for the Biomedical Sciences 4th EditionSuurem pilt
  • Formaat: 272 pages, Charts: 6 B&W, 0 Color; Drawings: 4 B&W, 0 Color; Tables: 0 B&W, 0 Color; Graphs: 39 B&W, 0 Color
  • Ilmumisaeg: 28-Aug-2009
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 047049686X
  • ISBN-13: 9780470496862
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470496862

Basic Statistics

A Primer for the Biomedical Sciences

Fourth Edition

Olive Jean Dunn

Virginia A. Clark

A new edition of a classic guide to statistical applications in the biomedical sciences

In the last decade, there have been significant changes in the way statistics is incorporated into biostatistical, medical, and public health research. Addressing the need for a modernized treatment of these statistical applications, Basic Statistics, Fourth Edition presents relevant, up-to-date coverage of research methodology using careful explanations of basic statistics and how they are used to address practical problems that arise in the medical and public health settings. Through concise and easy-to-follow presentations, readers will learn to interpret and examine data by applying common statistical tools, such as sampling, random assignment, and survival analysis.

Continuing the tradition of its predecessor, this new edition outlines a thorough discussion of different kinds of studies and guides readers through the important, related decision-making processes such as determining what information is needed and planning the collections process. The book equips readers with the knowledge to carry out these practices by explaining the various types of studies that are commonly conducted in the fields of medical and public health, and how the level of evidence varies depending on the area of research. Data screening and data entry into statistical programs is explained and accompanied by illustrations of statistical analyses and graphs. Additional features of the Fourth Edition include:

  • A new chapter on data collection that outlines the initial steps in planning biomedical and public health studies

  • A new chapter on nonparametric statistics that includes a discussion and application of the Sign test, the Wilcoxon Signed Rank test, and the Wilcoxon Rank Sum test and its relationship to the Mann-Whitney U test

  • An updated introduction to survival analysis that includes the Kaplan Meier method for graphing the survival function and a brief introduction to tests for comparing survival functions

  • Incorporation of modern statistical software, such as SAS®, Stata®, SPSS®, and Minitab® into the presented discussion of data analysis

  • Updated references at the end of each chapter

Basic Statistics, Fourth Edition is an ideal book for courses on biostatistics, medicine, and public health at the upper-undergraduate and graduate levels. It is also appropriate as a reference for researchers and practitioners who would like to refresh their fundamental understanding of statistical techniques.

Preface to the Fourth Edition.
1 Initial Steps.
1.1 Reasons for Studying Biostatistics.
1.2 Initial Steps in Designing a Biomedical Study.
1.3 Common Types of Biomedical Studies.
Problems.
References.
2 Populations and Samples.
2.1 Basic Concepts.
2.2 Definitions of Types of Samples.
2.3 Methods of Selecting Simple Random Samples.
2.4 Application of Sampling Methods in Biomedical Studies.
Problems.
References.
3 Collecting and Entering Data.
3.1 Initial Steps.
3.2 Data Entry.
3.3 Screening the Data.
3.4 Code Book.
Problems.
References.
4 Frequency Tables and Their Graphs.
4.1 Numerical Methods of Organizing Data.
4.2 Graphs.
Problems.
References.
5 Measures of Location and Variability.
5.1 Measures of Location.
5.2 Measures of Variability.
5.3 Sampling Properties of the Mean and Variance.
5.4 Considerations in Selecting Appropriate Statistics.
5.5 A Common Graphical Method for Displaying Statistics.
Problems.
References.
6 The Normal Distribution.
6.1 Properties of the Normal Distribution.
6.2 Areas Under the Normal Curve.
6.3 Importance of the Normal Distribution.
6.4 Examining Data for Normality.
6.5 Transformations.
Problems.
References.
7 Estimation of Population Means: Confidence Intervals.
7.1 Confidence Intervals.
7.2 Sample Size Needed for a Desired Confidence Interval.
7.3 The t Distribution.
7.4 Confidence Interval for the Mean, Using the t Distribution.
7.5 Estimating the Difference Between Two Means: Unpaired Data.
7.6 Estimating the Difference Between Two Means: Paired Comparison.
Problems.
References.
8 Tests of Hypotheses on Population Means.
8.1 Tests of Hypotheses for a Single Mean.
8.2 Tests for Equality of two Means: Unpaired Data.
8.3 Testing for Equality of Means: Paired Data.
8.4 Concepts Used in Statistical Testing.
8.5 Sample Size.
8.6 Confidence Intervals Versus Tests.
8.7 Correcting for Multiple Testing.
8.8 Reporting the Results.
Problems.
References.
9 Variances: Estimation and Tests.
9.1 Point Estimates for Variances and Standard Deviations.
9.2 Testing Whether Two Variances Are Equal: F Test.
9.3 Approximate t Test.
9.4 Other Tests.
Problems.
References.
10 Categorical Data: Proportions.
10.1 Single Population Proportion.
10.2 Samples from Categorical Data.
10.3 The Normal Approximation to the Binomial.
10.4 Confidence Intervals for a Single Population Proportion.
10.5 Confidence Intervals for the Difference in Two Proportions.
10.6 Tests of Hypothesis for Population Proportions.
10.7 Sample Size for Testing Two Proportions.
10.8 Data Entry and Analysis Using Statistical Programs.
Problems.
References.
11 Categorical Data: Analysis of Two-Way Frequency Tables.
11.1 Different Types of Tables.
11.2 Relative Risk and Odds Ratio.
11.3 Chi-Square Tests for Frequency Tables: two-by-two Tables.
11.4 Chi-Square Tests for Larger Tables.
11.5 Remarks.
Problems.
References.
12 Regression and Correlation.
12.1 The Scatter Diagram: Single Sample.
12.2 Linear Regression: Single Sample.
12.3 The Correlation Coefficient for two Variables from a Single Sample.
12.4 Linear Regression Assuming the Fixed-X Model.
12.5 Other Topics in Linear Regression.
Problems.
References.
13 Nonparametric Statistics.
13.1 The Sign Test.
13.2 The Wilcoxon Signed Rank Test.
13.3 The Wilcoxon-Mann-Whitney Test.
13.4 Spearman’s Rank Correlation.
Problems.
References.
14 Introduction to Survival Analysis.
14.1 Survival Analysis Data.
14.2 Survival Functions.
14.3 Computing Estimates of f(t), S(t), and h(t).
14.4 Comparison of Clinical Life Tables and the Kaplan-Meier Method.
14.5 Additional Analyses Using Survival Data.
Problems.
References.
Appendix A: Statistical Tables.
Appendix B: Answers to Selected Problems.
Appendix C: Computer Statistical Program Resources.
C.1 Computer Systems for Biomedical Education and Research.
C.2 A Brief Indication of Statistics Computer Program Advances and Some Relevant Publications Since 2000.
C.3 Choices of Computer Statistical Software.
Bibliography.
Index.
The late OLIVE JEAN DUNN, PhD, was Professor Emerita of Biostatistics and Biomathematics at the University of California, Los Angeles. Dr. Dunn's academic career spanned over forty years and included significant contributions to statistical research. She was a Fellow of the American Statistical Association, the American Association for the Advancement of Science, and the American Public Health Association, as well as coauthor of Applied Statistics: Analysis of Variance and Regression, Third Edition (Wiley).

VIRGINIA A. CLARK, PhD, is Professor Emerita of Biostatistics and Biomathematics at the University of California, Los Angeles. A Fellow of the American Statistical Association, Dr. Clark has coauthored over ninety journal articles and is coauthor of Applied Statistics: Analysis of Variance and Regression, Third Edition (Wiley).
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