CONTENTS
- Preface to the Second Edition.
- Preface to the First Edition
- About the companion website.
- Descriptive Methods for Categorical Data
- Proportions
- Rates
- Ratios
- Notes on Computations
- Descriptive Methods for Continuous Data
- Tabular and graphical methods
- Numerical Methods
- A special case of binary data
- Coefficients of Correlation
- Notes on Computations
- Probability and Probability Models
- Probability
- Normal Distribution
- Probability Models for Continuous Data
- Probability Models for Discrete Data
- Brief Notes on the Fundamentals
- Notes on Computations
- Estimation of Parameters
- Basic Concepts
- Estimation of Means
- Estimation of Proportions
- Estimation of Odds Ratios
- Estimation of Correlation Coefficients
- Brief Notes on the Fundamentals
- Notes on Computations
- Introduction to Statistical Tests of Significance
- Basic Concepts
- Analogies
- Summaries and Conclusions
- Brief Notes on the Fundamentals
- Comparison of Population Proportions
- A one-sample problem with binary data
- Analysis of Pair-Matched Data
- Comparison of Two Proportions
- Mantel–Haenszel Method
- Inferences for General Two-Way Tables: 6.6 Fisher’s Exact Test
- Ordered 2 × K Contingency Tables 6. Eight Notes on Computations
- Comparison of Population Means
- One‐Sample Problem with Continuous Data
- Analysis of Pair-Matched Data
- Comparison of Two Means
- Nonparametric Methods
- One‐Way Analysis of Variance
- Brief Notes on the Fundamentals
- Notes on Computations
- Analysis of Variance
- Regression Analysis
- Logistic Regression
- Methods for Count Data
- Methods for Repetitively Measured Responses
- Analysis of Survival Data and Data from Matched Studies
- Study Designs
- References
- Appendices
- Answers to Selected Exercises
- Index
PREFACE
Professional students in public health, dentistry, nursing, and medicine, as well as graduate students in nursing and other biological sciences, typically require introductory biostatistics courses; this requirement is often perceived as a barrier and source of concern in certain fields.
There are numerous ways to articulate these emotions, but they all ultimately lead to the same conclusion: Students need help in the form of easy-to-use and accurate knowledge-based text to provide adequate energy. Understand the study of a subject that is considered difficult and dry. We have written this introductory text to assist human health professionals and students in successfully completing the basic biology requirements of a semester or two-year course. Our primary goal is to shift the perspective from viewing mathematics as a mere series of exercises for students to complete to viewing it as a method of thinking. This involves considering how we can gather and evaluate data to enhance our understanding of the required lessons. We base the book on real data, providing a wealth of factual information through examples and exercises in the various chapters to aid in the application of statistical methods. Basic mathematics still plays a crucial role in this process.
The first five chapters are a slow, easy-to-use approach to nurturing interest and motivation to learn. We occasionally add chapters called “Notes on Basics” to gradually reinforce the history and concepts. We will increase the tempo in the remaining seven sessions to ensure that those who take two courses throughout the year have sufficient knowledge of the course’s basic principles. Our basic strategy is that most students only need one lesson, which ends in the middle of Chapter 9, after repeating a simple rule; after that, teachers can add several chapters to Chapter 14.
For students studying only one course, other sections can serve to support course discussions and meet their future needs. A group of students with a strong background in mathematics moves on to the second course and can navigate the remaining chapters with the help of a short article on the basics. A unique feature of the book is the ‘Text to Count’ section, located at the end of most chapters. These notes cover the use of Microsoft Excel, but examples of SAS computer programs are also included in the appendices of many examples, particularly on topics covered in previous chapters.
Mathematical thinking has become important not only for those working in science or business but also for all professionals who care about making the world a better place. So, what exactly is biostatistics, and what can it accomplish? Mathematics has familiar definitions and concepts. We see ‘vital figures’ in the news—announcements of life events such as births, marriages, and deaths. We advise drivers to drive cautiously to prevent this from turning into a “statistic.”
People frequently use the word “general” to refer to a number or list of information. We have also heard people use the term “data” to describe a verbal report or an accepted anecdote. In this book, particularly in the initial chapters, we do not emphasize numbers as objects but instead present a practical approach to handling numbers in the context of the trade. These are necessary, but they’re not all you need to know. To demonstrate the concept of statistics as a way of thinking, let’s begin with the most prevalent example: criminal proceedings. Investigators discovered the crime and identified the suspect. Following a police investigation to gather evidence against a suspect, the prosecutor presents a summary of the evidence to the jury. The unanimous decision gives the jury members the rules for winning without hesitation, and then the discussion commences. The judges deliberated, cast their votes, and rendered a verdict: guilty or not guilty. Why do we need this time-consuming, expensive process to conduct a jury trial? The truth frequently remains elusive, especially when uncertainty arises. Possibly only the suspect knows the truth, but they won’t say. The uncertainty stems from the variability of each case, which is unique, and the absence of certain data. Jury trials are our society’s way of dealing with questionable cases; their purpose is to reduce errors.
How does society deal with uncertainty? We go through the jury process, which consists of the following steps: The jury process involves (1) formulating a hypothesis based on the principle of innocence until proven guilty, (2) collecting evidence against the suspect, and (3) determining the validity of the hypothesis to determine if the suspect is guilty or not. With a well-developed system, sometimes we do well, and sometimes we don’t. In principle, a successful case must have all of the following elements: (1) probable cause (with the crime and the suspect), (2) a thorough investigation by the police, (3) a competent presentation by the prosecutor, and (4) a fair and impartial jury. Let’s look at a few specific examples in the context of a jury trial: (1) The crime is lung cancer, and the suspect is a smoker, or (2) the crime is leukemia, and the suspect uses pesticides, or (3) the crime is breast cancer, and the suspect has a defective gene. We now refer to this process as research, and biostatistics serves as the tool for conducting it. In its most basic form, biostatistics functions similarly to statistics and its biomedical counterpart.
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