A Handbook of Numerical and Statistical Techniques: With Examples Mainly from the Life Sciences

CUP Archive, Nov 29, 1979 - Mathematics - 349 pages
This handbook is designed for experimental scientists, particularly those in the life sciences. It is for the non-specialist, and although it assumes only a little knowledge of statistics and mathematics, those with a deeper understanding will also find it useful. The book is directed at the scientist who wishes to solve his numerical and statistical problems on a programmable calculator, mini-computer or interactive terminal. The volume is also useful for the user of full-scale computer systems in that it describes how the large computer solves numerical and statistical problems. The book is divided into three parts. Part I deals with numerical techniques and Part II with statistical techniques. Part III is devoted to the method of least squares which can be regarded as both a statistical and numerical method. The handbook shows clearly how each calculation is performed. Each technique is illustrated by at least one example and there are worked examples and exercises throughout the volume.

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Contents

 STATISTICAL TABLES 4 Errors mistakes and the arrangement of work 14 Simple methods for smoothing crude data 26 The area under a curve 37 Finite differences interpolation and numerical differentiation 44 Some other numerical techniques 60 Probability statistical distributions and moments 75 The normal and related distributions 90
 Fishers ztransformation table 12 31 1 200 Point and interval estimation 210 Some special statistical techniques 236 1S Simple linear regression and the method of least squares 255 Curvilinear regression 275 Multiple linear regression 300 Nonlinear regression 313 Appendix 321

 The common discrete distributions 100 The Pearson system of probabilitydensity functions 122 Hypothesis testing 133 The upper 100a per cent points of the KolmogorovSmirnov distribution 153 The upper 100a per cent points of the KruskalWallis distribution table 180
 A3 Students distribution 327 Coefficients of optimalsmoothing runningaverage formulae table 4 2 3 30 334 Author index 337 Copyright

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Page xi - The expected value of the dependent variable for a given value of the. independent variable is, 3) For any given value of X, the observed y values are distributed independently and normally.