Our search has the following Google-type functionality:
If you use '+' at the start of a word, that word will be present in the search results.
eg. Harry +Potter
Search results will contain 'Potter'.
If you use '-' at the start of a word, that word will be absent in the search results.
eg. Harry -Potter
Search results will not contain 'Potter'.
If you use 'AND' between 2 words, then both those words will be present in the search results.
eg. Harry AND Potter
Search results will contain both 'Harry' and 'Potter'.
NOTE: AND will only work with single words not phrases.
If you use 'OR' between 2 single words, then either or both of those words will be present in the search results.
eg. 'Harry OR Potter'
Search results will contain just 'Harry', or just 'Potter', or both 'Harry' and 'Potter'.
NOTE: OR will only work with single words not phrases.
If you use 'NOT' before a word, that word will be absent in the search results. (This is the same as using the minus symbol).
eg. 'Harry NOT Potter'
Search results will not contain 'Potter'.
NOTE: NOT will only work with single words not phrases.
If you use double quotation marks around words, those words will be present in that order.
eg. "Harry Potter"
Search results will contain 'Harry Potter', but not 'Potter Harry'.
NOTE: "" cannot be combined with AND, OR & NOT searches.
If you use '*' in a word, it performs a wildcard search, as it signifies any number of characters. (Searches cannot start with a wildcard).
Search results will contain words starting with 'Pot' and ending in 'er', such as 'Potter'.
Mark Chang is vice president of biometrics at AMAG Pharmaceuticals and an adjunct professor at Boston University. Dr. Chang is an elected fellow of the American Statistical Association and a co-founder of the International Society for Biopharmaceutical Statistics. He serves on the editorial boards of statistical journals and has published seven books in biostatistics and science, including Paradoxes in Scientific Inference, Modern Issues and Methods in Biostatistics, Adaptive Design Theory and Implementation Using SAS and R, and Monte Carlo Simulation for the Pharmaceutical Industry.
This book is designed not only for a conceptual understanding of scientific fundamental principles behind the methods, but also to introduce some innovative applications from different fields. The book fits for a wide range of audiences who do not have any mathematics or statistics backgrounds. As written by an experienced statistician from pharmaceutical industry, the book provides an insightful overview of the current practices of experimentation and statistical inferences in pharmaceutical drug development, and also the concepts and rationales of the innovative methods beyond the pharmaceutical research and development. This is a useful reference book to inspire the readers of creative thinking by the great ideas behind the scientific methods. ... In summary, this is a useful reference book on understanding the scientific principles. This book contains a very good collection of innovative scientific methods and applications. The intuitive figures and diagrams are helpful to understand the concepts and the italic-face font for the definitions facilitates the review. -Journal of Biopharmaceutical Statistics, 2015 ... the section on misconceptions and pitfalls in statistics is a must-read. ... The book is at its best when discussing examples, paradoxical questions, or philosophical issues, and Chang puts good emphasis on statistics-related topics: publication bias, the Monty Hall problem, regression to the mean, and multiple testing issues all find a place for discussion. -Significance, February 2015 ... best used as a text for a course in the principles of scientific methods for both students in science and the humanities, and instructors could expand in their lectures on material that the book expresses in a lapidary style. Moreover, even those who use the book for self-study would find that the extra effort they may need to devote to the work would be well rewarded. Summing Up: Recommended. Lower-division undergraduates through researchers/faculty. -R. Bharath, Northern Michigan University in CHOICE March 2015, Vol. 52 No. 7 As researchers interested in medicine, theoretical mathematical statistics can be somewhat grim and distant from professional medical activity, closer to the world of biology. However, Principles of Scientific Methods, by Mark Chang, discusses in a way comprehensible for nonmathematical professionals, the paradigms behind the methods of scientific research, such as the current mode of so called `evidence-based medicine'. It is an excellent work to introduce people to principles of research, with plentiful graphics. -Journal of Applied Statistics, February 28, 2017