GS 535: Statistical Methods in Geosciences

Syllabus​

Introduction to probability: random experiments, events, sample space, definitions of probability. Conditional probability and independence of events, Bayes theorm. Random variables, discrete and continuous probability distributions, joint probability distributions, conditional probability distributions. Mathematical expectation, moment generating and characteristic functions. Binomial, Poisson, Normal, Gamma, Exponential, Hypergeometric, Multinomial, Chi-square, t, and F distributions. Introduction to statistical inference, sampling distributions, point and interval estimation, hypothesis testing involving one and two univariate populations. Linear models ANOVA. Linear and multiple regression. Introduction to multivariate techniques PCA, factor analysis, linear discriminant analysis, classification. 

Texts/References

  • Ross, S.M. Introduction to probability and statistics for engineers and scientists. Elsevier,2004
  • Spiegel, M.R. Probability and Statistics, Schaums Outline Series, McGraw-Hill Intl., Singapore,Asian Student edn., 1982
  • Davis, J.C. Statistics and data analysis in geology, John Wiley, 1986
  • Walpole, R.E. and Myers, R.H. Probability and statistics for engineers and scientists, Macmillan Publ. Co., 1989
  • Johnson, R.A. and Wichern, D.W. Applied multivariate statistical analysis, Prentice Hall Inc.,New Jersey, 1982
  • Hardle W. Applied multivariate statistical analysis. Springer, 2003