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Author Marques de Sรก, Joaquim P. author Applied Statistics Using SPSS, STATISTICA and MATLAB [electronic resource] / by Joaquim P. Marques de Sรก Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003 http://dx.doi.org/10.1007/978-3-662-05804-6 XXII, 452 p. 156 illus. online resource

SUMMARY

This books is intended for students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA. The book provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages in a pedagogical way. It provides guidance on how to use SPSS, MATALB and STATISTICA in statistical analysis applications without having to delve in the manuals. The accompanying CD-Rom includes several specific software tools for the topics described in the book, including a set of MATLAB functions for directional statistics as well as the data sets used in the examples and exercises covering a broad spectrum of areas from engineering, medicine, biology, psychology, economy, geology, and astronomy

CONTENT

1 Introduction -- 2 Presenting and Summarising the Data -- 3 Estimating Data Parameters -- 4 Parametric Tests of Hypotheses -- 5 Non-Parametric Tests of Hypotheses -- 6 Statistical Classification -- 7 Data Regression -- 8 Data Structure Analysis -- 9 Survival Analysis -- 10 Directional Data -- Appendix A โ{128}{148} Short Survey on Probability Theory -- A.1 Basic Notions -- A.1.1 Events and Frequencies -- A.1.2 Probability Axioms -- A.2 Conditional Probability and Independence -- A.2.1 Conditional Probability and Intersection Rule -- A.2.2 Independent Events -- A.3 Compound Experiments -- A.4 Bayesโ{128}{153} Theorem -- A.5 Random Variables and Distributions -- A.5.1 Definition of Random Variable -- A.5.2 Distribution and Density Functions -- A.5.3 Transformation of a Random Variable -- A.6 Expectation, Variance and Moments -- A.6.1 Definitions and Properties -- A.6.2 Moment-Generating Function -- A.6.3 Chebyshev Theorem -- A.7 The Binomial and Normal Distributions -- A.7.1 The Binomial Distribution -- A.7.2 The Laws of Large Numbers -- A.7.3 The Normal Distribution -- A.8 Multivariate Distributions -- A.8.1 Definitions -- A.8.2 Moments -- A.8.3 Conditional Densities and Independence -- A.8.4 Sums of Random Variables -- A.8.5 Central Limit Theorem -- Appendix B โ{128}{148} Distributions -- B.1 Discrete Distributions -- B.1.1 Bernoulli Distribution -- B.1.2 Uniform Distribution -- B.1.3 Geometric Distribution -- B.1.4 Hypergeometric Distribution -- B.1.5 Binomial Distribution -- B.1.6 Multinomial Distribution -- B.1.7 Poisson Distribution -- B.2 Continuous Distributions -- B.2.1 Uniform Distribution -- B.2.2 Normal Distribution -- B.2.3 Exponential Distribution -- B.2.4 Weibull Distribution -- 6.2.5 Gamma Distribution -- B.2.6 Beta Distribution -- B.2.7 Chi-Square Distribution -- B.2.8 Studentโ{128}{153}s t Distribution -- B.2.9 F Distribution -- B.2.10 Von Mises Distributions -- Appendix C โ{128}{148} Point Estimation -- C.1 Definitions -- C.2 Estimation of Mean and Variance -- Appendix D โ{128}{148} Tables -- D.1 Binomial Distribution -- D.2 Normal Distribution -- D.4 Chi-Square Distribution -- Appendix E โ{128}{148} Datasets -- E.1 Breast Tissue -- E.2 Car Sale -- E.3 Cells -- E.4 Clays -- E.5 Cork Stoppers -- E.6 CTG -- E.7 Culture -- E.8 Fatigue -- E.9 FHR -- E.10 FHR-Apgar -- E.11 Firms -- E.12 Flow Rate -- E.13 Foetal Weight -- E.14 Forest Fires -- E.15 Freshmen -- E.16 Heart Valve -- E.17 Infarct -- E.18 Joints -- E.19 Metal Firms -- E.20 Meteo -- E.21 Moulds -- E.22 Neonatal -- E.23 Programming -- E.24 Rocks -- E.25 Signal & Noise -- E.26 Soil Pollution -- E.27 Stars -- E.28 Stock Exchange -- E.29 VCG -- E.30 Wave -- E.31 Weather -- E.32 Wines -- Appendix F โ{128}{148} Tools -- F.1 MATLAB Functions -- F.2 Tools EXCEL File -- F.3 SCSIZE Program -- References

Mathematics Probabilities Statistics Applied mathematics Engineering mathematics Computational intelligence Complexity Computational Mathematics Probability Theory and Stochastic Processes Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences Computational Intelligence Complexity Appl.Mathematics/Computational Methods of Engineering

Location

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