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9781119089995 English 1119089999 A practical and methodological approach to the statistical logic of biostatistics in the field of health research Focusing on a basic understanding of the methods and analyses in health research, "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "provides statistical concepts for interpreting results using Excel. The book emphasizes the application of methods and presents the most common methodological procedures in health research, which includes multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. The book is constructed around a flowchart that outlines the appropriate circumstances for selecting a method to analyze a specific set of data. Beginning with an introduction to the foundational methods of statistical logic before moving on to more complex methods, "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "also includes: Detailed discussions of how knowledge and skills in health research have been integrated with biostatistical methods Numerous examples with clear explanations that use mostly real-world health research data in order to provide a better understanding of the practical applications Implements Excel graphic representations throughout to help readers evaluate and analyze individual results An appendix with basic information on how to use Excel A companion website with additional Excel files, data sets, and homework problems as well as an Instructor's Solutions Manual "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "is an excellent textbook for upper-undergraduate and graduate-level courses in biostatistics and public health. In addition, the book is an appropriate reference for both health researchers and professionals., This book aids health research students in understanding statistics, both practically and methodogically. The author's approach views statistics as a language of logic rather than mathematics with the intention of helping readers understand the needed biostatistical concepts. The most common methodogical procedures in health research are featured, including multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. The book focuses on interpretation of the results of statistical analyses instead of the mechanics, and Excel is utilized throughout to evaluate results. Relevant screenshots are provided in an effort for students to evaluate their own analyses. One important topic usually overlooked in statistical textbooks is how to select the appropriate statistical method to analyze a particular set of data. Dr. Hirsch's book is constructed around a flowchart that demonstrates how a statistician selects a method to analyze a specific set of data, allowing students to appreciate the circumstance in which each statistical method is the appropriate choice. The book is divided into four sections: Basic Principles of Biostatistics; Univariable Analysis; Bivariable Analysis; and Multivariable Analysis.
9781119089995 English 1119089999 A practical and methodological approach to the statistical logic of biostatistics in the field of health research Focusing on a basic understanding of the methods and analyses in health research, "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "provides statistical concepts for interpreting results using Excel. The book emphasizes the application of methods and presents the most common methodological procedures in health research, which includes multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. The book is constructed around a flowchart that outlines the appropriate circumstances for selecting a method to analyze a specific set of data. Beginning with an introduction to the foundational methods of statistical logic before moving on to more complex methods, "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "also includes: Detailed discussions of how knowledge and skills in health research have been integrated with biostatistical methods Numerous examples with clear explanations that use mostly real-world health research data in order to provide a better understanding of the practical applications Implements Excel graphic representations throughout to help readers evaluate and analyze individual results An appendix with basic information on how to use Excel A companion website with additional Excel files, data sets, and homework problems as well as an Instructor's Solutions Manual "Introduction to Biostatistical Applications in Health Research with Microsoft(R) Office Excel(R) "is an excellent textbook for upper-undergraduate and graduate-level courses in biostatistics and public health. In addition, the book is an appropriate reference for both health researchers and professionals., This book aids health research students in understanding statistics, both practically and methodogically. The author's approach views statistics as a language of logic rather than mathematics with the intention of helping readers understand the needed biostatistical concepts. The most common methodogical procedures in health research are featured, including multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. The book focuses on interpretation of the results of statistical analyses instead of the mechanics, and Excel is utilized throughout to evaluate results. Relevant screenshots are provided in an effort for students to evaluate their own analyses. One important topic usually overlooked in statistical textbooks is how to select the appropriate statistical method to analyze a particular set of data. Dr. Hirsch's book is constructed around a flowchart that demonstrates how a statistician selects a method to analyze a specific set of data, allowing students to appreciate the circumstance in which each statistical method is the appropriate choice. The book is divided into four sections: Basic Principles of Biostatistics; Univariable Analysis; Bivariable Analysis; and Multivariable Analysis.