Principles and applications of biostatistics
著者
書誌事項
Principles and applications of biostatistics
Jones & Bartlett Learning, c2022
- : pbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Principles and Applications of Biostatistics covers the primary concepts and methods that are required for a fundamental understanding of the use and interpretation of statistics for the biological and health sciences. The text presents ways in which biostatistics can effectively describe and assess problems (e.g., COVID-19) that threaten physical, mental, and social wellbeing. Data collection, analysis, presentation, and interpretation are covered in detail and supported with ample relevant examples and exercises incorporated throughout the book.
Key Features:
Principles and Applications of Biostatistics covers the primary concepts and methods that are required for a fundamental understanding of the use and interpretation of statistics for the biological and health sciences. The text presents ways in which biostatistics can effectively describe and assess problems (e.g., COVID-19) that threaten physical, mental, and social wellbeing. Data collection, analysis, presentation, and interpretation are covered in detail and supported with ample relevant examples and exercises incorporated throughout the book.
Key Features:
* Practical questions follow each problem to encourage students to consider why the problem likely exists, help formulate hypotheses, and then statistically assess those hypotheses.
* Abundant examples and assignment problems (many involving COVID-19) within each chapter cover a variety of application areas of biostatistics.
* Well-designed, attractive graphics that help make statistics easier to comprehend are used to present concepts, functions, and data.
* Applied focus encourages students to use computer applications (e.g. SAS MS Excel) to demonstrate data analysis.
* Data analysis systems are used to obtain descriptive measures and basic plots (e.g. stem-and-leaf and box plots) for the purposes of exploratory data analysis.
* P-values in hypothesis testing and confidence intervals in descriptive and analytic assessment are discussed and included on many of the computer printouts.
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