The discipline of Statistics Introduction and terminology

It is common to start a textbook with a definition of the book s topic, ffowever, in the case of the discipline of Statistics (indicated in this book with a capital S ), it is difficult to find a universally accepted definition. Different textbooks are written for different target audiences, and their goals can therefore be quite different. So, before going any further, it is appropriate to identify our target audiences, and to provide you with a definition of Statistics that is informative and meaningful in the context of this book. 

The discipline of Statistics is discussed in the context of pharmaceutical clinical trials because two of the primary target audiences for this book are students of pharmacy and students of clinical research. A clinical trial can be defined as an experiment testing a medical treatment on humans (Piantadosi, 2005). In this definition, the words human and clinical are closely linked. However, this definition also makes it clear that clinical trials can be performed to test a variety of medical treatments. In addition to pharmaceutical trials, the focus of this book, clinical trials are conducted to test medical devices (see Becker and Whyte, 2006) and some surgical practices. 

By teaching Statistics in a context that is very relevant to you, the statistical analyses that you will learn about will not simply be abstract ideas They will be techniques that meaningfully collect and analyze numerical information of importance in your profession. The development of new drugs, whether brand-new chemical entities (NCEs), biologies, or new forms of existing drugs, requires three steps  

decision-making based on this analysis and interpretation. 

By the end of this book you will have a solid conceptual knowledge and understanding of the experimental methods and statistical analyses used in new drug development. In addition, you will have gained computational knowledge You will have learned how to conduct the most commonly used statistical analyses and how to interpret the results of these analyses. This combination of conceptual and computational knowledge and understanding is a powerful one that will serve you well in the rest of your studies. 

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