Short background to why this book was written

Organic synthesis is an important area in chemical research. New synthetic methods are invented at an ever increasing rate which open up new ways to produce interesting chemical compounds. These factors are of tremendous importance for the practical use of synthetic methods both for academic research and for industrial applications. 

Knowledge of multivariate methods is not, however, widely spread in the community of synthesis chemists. Therefore, many new methods are still being investigated through poorly designed experiments and hence, new procedures are not properly optimized. Still, the most common method to carry out systematic studies is to consider one factor at a time , although such an approach was shown by R.A. Fisher to be inappropriate over 60 years ago [1], when several factors are to be considered. 

I believe that the reason why organic synthesis chemists do not apply statistical principles in their experiments is that they do not know how to use such methods. In general, they do not bother to read text-books on statistics because such books rarely describe how statistics may be relevant to their chemical problems. My personal experience may illustrate this When I started my chemical career some 20 years ago 

I am therefore convinced that there is a need for a book which spans a bridge between practical organic synthesis and statistics. Such a book must describe chemical problems as they are seen by the synthesis chemist and must introduce statistical tools so that the results obtained are chemically relevant to the chemist. The present book is a humble attempt to use these principles as guidelines. 

Professional statisticians may complain that this is yet another introductory text on statistics, written by a non-statistician. This is true, my devotion and professional training are in the field of synthetic chemistry. However, in exploring this field I felt a need for statistical principles to guide my way. This book is an attempt to transmit my personal experiences to my fellow colleagues. If anyone among them should respond to the message and be stimulated to learn more about statistics, I would feel that my mission as an evangelist had been succesful. 

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