Descriptive and Mathematical Statistics



Chapter 27 deals with basic theory and practical methods of statistical inference: 27.1. Sampling Theory: Simple Random Sample, 27.2. Sampling Theory: Stratified Random Sample, 27.3. Elementary Statistical Treatment, 27.4. Sample Quantiles, 27.5. Measures of Sample Level, 27.6. Measures of Sample Variability, 27.7. Measures of Sample Concentration, 27.8. Measures of Sample Dependence, 27.9. Point and Interval Estimators, 27.10. Hypothesis Testing, 27.11. Regression Analysis, 27.12. Analysis of Variance (ANOVA), 27.13. Multivariate Statistical Analysis.


Linear Discriminant Analysis Linear Regression Model Unbiased Estimator Discriminant Class Linear Unbiased Estimate 

Further Reading

  1. Draper, N.R., Smith, H.: Applied Regression Analysis. Wiley, New York (1998)MATHGoogle Scholar
  2. Jolliffe, I.T.: Principal Component Analysis. Springer, New York (2002)MATHGoogle Scholar
  3. Lehmann, E.L., Romano, J.P.: Testing Statistical Hypotheses. Springer, New York (2005)MATHGoogle Scholar
  4. Mardia, K.V., Kent, J.T., Bibby, J.M.: Multivariate Analysis. Academic, London (1979)MATHGoogle Scholar
  5. Rektorys, K. et al.: Survey of Applicable Mathematics. Kluwer, Dordrecht (1994)Google Scholar
  6. Rice, J.A.: Mathematical Statistics and Data Analysis. Duxbury Press, Boston, MA (1995)MATHGoogle Scholar
  7. Wasserman, L.: All of Nonparametric Statistics. Springer, New York (2006)MATHGoogle Scholar
  8. Wilks, S.S.: Mathematical Statistics. Wiley, New York (1962)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Dept. of Statistics, Faculty of Mathematics and PhysicsCharles University of PraguePragueCzech Republic

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