The core principles of statistical analysis are too easily forgotten in today’s world of powerful computers and time-saving algorithms. This step-by-step primer takes researchers who lack the confidence to conduct their own analyses right back to basics, allowing them to scrutinize their own data through a series of rapidly executed reckonings on a simple pocket calculator. A range of easily navigable tutorials facilitate the reader’s assimilation of the techniques, while a separate chapter on next generation Flash prepares them for future developments in the field. This practical volume also contains tips on how to deny hackers access to Flash internet sites. An ideal companion to the author’s co-authored works on statistical analysis for Springer such as Statistics Applied to Clinical Trials, this monograph will help researchers understand the processes involved in interpreting clinical data, as well as being a necessary prerequisite to mastering more advanced statistical techniques. The principles of statistical analysis are easily forgotten in today’s world of time-saving algorithms. This step-by-step primer takes researchers back to basics, enabling them to examine their own data through a series of sums on a simple pocket calculator.

Provides an elementary, yet thorough introduction to the central topics of numerical analysis and scientific computation. Contains many demonstrations and numerical experiments, and homework assignments involving numerical work, all designed to be carried out on a programmable pocket calculator, usually of the size of the HP-33E.

How THIS BOOK DIFFERS This book is about the calculus. What distinguishes it, however, from other books is that it uses the pocket calculator to illustrate the theory. A computation that requires hours of labor when done by hand with tables is quite inappropriate as an example or exercise in a beginning calculus course. But that same computation can become a delicate illustration of the theory when the student does it in seconds on his calculator. t Furthermore, the student's own personal involvement and easy accomplishment give hi~ reassurance and en couragement. The machine is like a microscope, and its magnification is a hundred millionfold. We shall be interested in limits, and no stage of numerical approximation proves anything about the limit. However, the derivative of fex) = 67.SgX, for instance, acquires real meaning when a student first appreciates its values as numbers, as limits of 10 100 1000 t A quick example is 1.1 , 1.01 , 1.001 , •••• Another example is t = 0.1, 0.01, in the function e/3t+9-3)/t. ix difference quotients of numbers, rather than as values of a function that is itself the result of abstract manipulation.

This textbook presents methods of data analysis and uncertainty estimation based on classical statistics whilst including the use of robust statistics, Monte Carlo modelling, informational criteria, and non-statistical methods. Related computer programs and their creative use are also discussed, without reference to specific packages. The book contains one hundred illustrations and numerous examples using real-world data, from a student lab to the latest scientific results. It will appeal to students, scientists, engineers, metrologists, and everyone interested in processing measurement results.

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