Principles of biostatistics [by] Marcello Pagano, Kimberlee Gauvreau [and] Heather Mattie

By:

Pagano, M

Contributor(s):

Publication details: New York CRC Press 2022Edition: 3rd edDescription: xvi, 604p. 24cmISBN:

978-0-367-35580-7

Subject(s):

Biometry; MEDICAL Biostatistics; MEDICAL Epidemiology; biometrics

DDC classification:

570.1 PAG

Contents:

1. IntroductionPart I Variability2. Descriptive Statistics3. Rates and Standardization4. Life TablesPart II Probability5. Probability6. Screening and Diagnostic Tests7. Theoretical Probability Distributions8. Sampling Distribution of the MeanPart III Inference9. Confidence Intervals10. Hypothesis Testing11. Comparison of Two Means12. Analysis of Variance13. Nonparametric Methods14. Inference on Proportions15. Contingency Tables16. Correlation17. Simple Linear Regression18. Multiple Linear Regression19. Logistic Regression20. Survival Analysis21. Sampling Theory22. Study DesignBibliographyGlossaryStatistical TablesIndex

Summary: Principles of Biostatistics, Third 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. Thoroughly revised and updated, this third edition includes a new chapter introducing the basic principles of Study Design, as well as new sections on sample size calculations for two-sample tests on means and proportions, the Kruskal-Wallis test, and the Cox proportional hazards model. Key Features: Includes a new chapter on the basic principles of study design. Additional review exercises have been added to each chapter. Datasets and Stata and R code are available on the book's website. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them

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Holdings ( 1 )
Title notes ( 2 )

Holdings
Item type	Current library	Shelving location	Call number	Status	Notes	Barcode
BOOKs	.	Circulation Counter	570.1 PAG (Browse shelf(Opens below))	Not For Loan	Recommended by Dr. Nivedita Nadkarni	39950

Principles of Biostatistics, Third 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. Thoroughly revised and updated, this third edition includes a new chapter introducing the basic principles of Study Design, as well as new sections on sample size calculations for two-sample tests on means and proportions, the Kruskal-Wallis test, and the Cox proportional hazards model. Key Features: Includes a new chapter on the basic principles of study design. Additional review exercises have been added to each chapter. Datasets and Stata and R code are available on the book's website. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them

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