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
- 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 at 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 at the Fundamentals
- Notes on Computations
- Introduction to Statistical Tests of Significance
- Basic Concepts
- Analogies
- Summaries and Conclusions
- Brief Notes at the Fundamentals
- Comparison of Population Proportions
- 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 at the Fundamentals
- Notes on Computations
- Analysis of Variance
- Regression Analysis
- Logistic Regression
- Methods for Count Data
- Methods for Repeatedly Measured Responses
- Analysis of Survival Data and Data from Matched Studies
- Study Designs
- References
- Appendices
- Answers to Selected Exercises
- Index
PREFACE
Introductory biostatistics courses are generally required for professional students in public health, dentistry, nursing, and medicine, as well as graduate students in nursing and other biological sciences; this is often considered a barrier and concern in some fields. These feelings are expressed in many ways and in different ways, but they all come 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. This introductory text is written for human health professionals and students who need help to succeed and benefit from the basic biology requirements of a semester or full two-year course. Our main aim is to avoid thinking of mathematics as a series of exercises that students must ‘get through’, but to present it as a way of thinking: thinking about how we can collect and analyze data to benefit from the follow-up of required lessons. There is no better way to do this than to base the book on real data; Therefore, a lot of factual information in the form of examples and exercises has been placed in the various chapters to assist in the use of statistical methods. There are still nuts and bolts of basic mathematics in use.
The first five chapters are a slow, easy-to-use approach to nurturing interest and motivation to learn. Chapters called “Notes on Basics” are occasionally added to gradually reinforce the history and concepts. The tempo will be increased in the remaining seven sessions to ensure that those who take two courses throughout the year have sufficient knowledge of the basic principles of the course. Our basic strategy is that most students only need one lesson, ending in the middle of Chapter 9, after repeating a simple rule; 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 move 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 people who want to help make the world a better place. So, what is biostatistics and what can it do? Mathematics has familiar definitions and concepts. We see ‘vital figures’ in the news: announcements of life events such as births, marriages, deaths. Drivers are advised to drive carefully to avoid this becoming a ‘statistic’.
The use of the word general is very variable and usually refers to a number or list of information. We have also heard people use the word data to describe a verbal report, an accepted anecdote. In this book, especially in the first few chapters, we do not emphasize numbers as objects, but instead offer a practical idea of ”doing numbers.” tools of the trade; These are necessary, but they’re not all you need to know. To show that statistics is a way of thinking, let’s start with the most common: criminal proceedings. The crime was discovered and the suspect was identified. Following a police investigation to gather evidence against a suspect, the prosecutor presents a summary of the evidence to the jury. In the unanimous decision, the jury members are given the rules for winning without hesitation, and then the discussion begins. After deliberation, the judges voted and a verdict was made: guilty or not guilty. Why do we need this time-consuming, expensive process to conduct a jury trial? One reason for this is that the truth is often unknown, at least when in doubt. Maybe the suspect is the only person who knows but won’t talk. It is uncertain due to variability (each case is different) and missing data. Jury trials are our society’s way of dealing with questionable cases; Its purpose is to reduce errors.
How does society deal with uncertainty? We go through the jury process, which consists of the following steps: (1) forming a hypothesis (everyone is innocent until proven innocent), (2) gathering information (evidence against the suspect), and (3) deciding whether the hypothesis is valid should be rejected (guilty) or not (not guilty). With a well-developed system, sometimes we do well, 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 good 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. This process is now called research, and the tool to conduct that research is biostatistics. In its simplest form, biostatistics works like statistics and the biomedical version of statistics. This is information .
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