Jingmei Jiang

Applied Medical Statistics (eBook, PDF)

• Format: PDF

Produktbeschreibung

APPLIED MEDICAL STATISTICS An up-to-date exploration of foundational concepts in statistics and probability for medical students and researchers Medical journals and researchers are increasingly recognizing the need for improved statistical rigor in medical science. In Applied Medical Statistics, renowned statistician and researcher Dr. Jingmei Jiang delivers a clear, coherent, and accessible introduction to basic statistical concepts, ideal for medical students and medical research practitioners. The book will help readers master foundational concepts in statistical analysis and assist in the development of a critical understanding of the basic rationale of statistical analysis techniques. The distinguished author presents information without assuming the reader has a background in specialized mathematics, statistics, or probability. All of the described methods are illustrated with up-to-date examples based on real-world medical research, supplemented by exercises and case discussions to help solidify the concepts and give readers an opportunity to critically evaluate different research scenarios. Readers will also benefit from the inclusion of: * A thorough introduction to basic concepts in statistics, including foundational terms and definitions, location and spread of data distributions, population parameters estimation, and statistical hypothesis tests * Explorations of commonly used statistical methods, including t-tests,analysis of variance, and linear regression * Discussions of advanced analysis topics, including multiple linear regression and correlation, logistic regression, and survival analysis * Substantive exercises and case discussions at the end of each chapter Perfect for postgraduate medical students, clinicians, and medical and biomedical researchers, Applied Medical Statistics will also earn a place on the shelf of any researcher with an interest in biostatistics or applying statistical methods to their own field of research.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 592
• Erscheinungstermin: 1. April 2022
• Englisch
• ISBN-13: 9781119716778
• Artikelnr.: 63731081

Autorenporträt

Jingmei Jiang, PhD, is Professor of Biostatistics, as well as a Doctoral Tutor in the Institute of Basic Medical Sciences (IBMS) of the Chinese Academy of Medical Sciences (CAMS) and School of Basic Medicine of Peking Union Medical College (PUMC). She has edited or co-edited seven academic monographs on biostatistics, and is also an editorial board member of several international journals. She is undertaking several research projects at the National Natural Science Foundation of China and other agencies.

Inhaltsangabe

Preface xiii

Acknowledgments xv

About the Companion Website xvii

1 What is Biostatistics 1

1.1 Overview 1

1.2 Some Statistical Terminology 2

1.2.1 Population and Sample 2

1.2.2 Homogeneity and Variation 3

1.2.3 Parameter and Statistic 4

1.2.4 Types of Data 4

1.2.5 Error 5

1.3 Workflow of Applied Statistics 6

1.4 Statistics and Its Related Disciplines 6

1.5 Statistical Thinking 7

1.6 Summary 7

1.7 Exercises 8

2 Descriptive Statistics 11

2.1 Frequency Tables and Graphs 12

2.1.1 Frequency Distribution of Numerical Data 12

2.1.2 Frequency Distribution of Categorical Data 16

2.2 Descriptive Statistics of Numerical Data 17

2.2.1 Measures of Central Tendency 17

2.2.2 Measures of Dispersion 26

2.3 Descriptive Statistics of Categorical Data 31

2.3.1 Relative Numbers 31

2.3.2 Standardization of Rates 34

2.4 Constructing Statistical Tables and Graphs 38

2.4.1 Statistical Tables 38

2.4.2 Statistical Graphs 40

2.5 Summary 47

2.6 Exercises 48

3 Fundamentals of Probability 53

3.1 Sample Space and Random Events 54

3.1.1 Definitions of Sample Space and Random Events 54

3.1.2 Operation of Events 55

3.2 Relative Frequency and Probability 58

3.2.1 Definition of Probability 59

3.2.2 Basic Properties of Probability 59

3.3 Conditional Probability and Independence of Events 60

3.3.1 Conditional Probability 60

3.3.2 Independence of Events 60

3.4 Multiplication Law of Probability 61

3.5 Addition Law of Probability 62

3.5.1 General Addition Law 62

3.5.2 Addition Law of Mutually Exclusive Events 62

3.6 Total Probability Formula and Bayes' Rule 63

3.6.1 Total Probability Formula 63

3.6.2 Bayes' Rule 64

3.7 Summary 65

3.8 Exercises 65

4 Discrete Random Variable 69

4.1 Concept of the Random Variable 69

4.2 Probability Distribution of the Discrete Random Variable 70

4.2.1 Probability Mass Function 70

4.2.2 Cumulative Distribution Function 71

4.2.3 Association Between the Probability Distribution and Relative Frequency Distribution 72

4.3 Numerical Characteristics 73

4.3.1 Expected Value 73

4.3.2 Variance and Standard Deviation 74

4.4 Commonly Used Discrete Probability Distributions 75

4.4.1 Binomial Distribution 75

4.4.2 Multinomial Distribution 80

4.4.3 Poisson Distribution 82

4.5 Summary 87

4.6 Exercises 87

5 Continuous Random Variable 91

5.1 Concept of Continuous Random Variable 92

5.2 Numerical Characteristics 93

5.3 Normal Distribution 94

5.3.1 Concept of the Normal Distribution 94

5.3.2 Standard Normal Distribution 96

5.3.3 Descriptive Methods for Assessing Normality 99

5.4 Application of the Normal Distribution 102

5.4.1 Normal Approximation to the Binomial Distribution 102

5.4.2 Normal Approximation to the Poisson Distribution 105

5.4.3 Determining the Medical Reference Interval 108

5.5 Summary 109

5.6 Exercises 110

6 Sampling Distribution and Parameter Estimation 113

6.1 Samples and Statistics 114

6.2 Sampling Distribution of a Statistic 114

6.2.1 Sampling Distribution of the Mean 115

6.2.2 Sampling Dist