Degree | Type | Year | Semester |
---|---|---|---|
2503852 Applied Statistics | OB | 4 | 0 |
The rules of permanence establish a minimum of 160 ECTS of the degree passed to be able to enroll in the Final Project.
See the Catalan version.
The final degree works (TFG) may be rather theoretical (some topic of statistics that is not worked on any of the subjects of the degree) or of a more practical nature (to study in depth a problem and / or specific data ). In the first case it will have to contain examples of practical application of the results studied. In the second case, it must contain an adequate theoretical foundation of the results that are used.
The student and the tutor will determine the content of the TFG when this subject begins. The work can be chosen from those proposed by the teachers of the degree or can be proposed by the same student within a line of interest offered by the professors of the Department of Mathematics or Sociology. In both cases you must have the approval of the degree coordinator.
The extension of the TFG can be variable but it is recommended between fifteen and thirty pages. The work can be presented in Catalan, Spanish or English. The first page will include a title, author and tutor, place and dates where the work is carried out. It will then follow a summary that will be in the same language of the text and with its English language version. Non-original content must have been clearly referenced in the bibliography that will appear at the end of the text.
See the Catalan version.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Bibliographic inquiry | 15 | 0.6 | |
Type: Autonomous | |||
autonomous learning | 59 | 2.36 | |
work completion | 225 | 9 |
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Contents | 80% | 0.5 | 0.02 | 7, 11, 1, 5, 6, 4, 8, 9, 14, 13, 12, 2, 3, 10 |
Debate | 10% | 0.25 | 0.01 | 11, 5, 9, 10 |
Presentation | 10% | 0.25 | 0.01 | 11, 5, 9, 10 |
Recommended bibliography:
GENERAL
Snedecor, G. W. and Cochran, W. G. (1989) Statistical Methods - The Iowa State University Press
Steel, R. and Torrie, J. H. (1976) Introduction to Statistics -McGraw-Hill
Steel, R. and Torrie, J. H. (1985) Bioestadística: principios y procedimientos - McGraw-Hill
ANOVA
Box, P., Hunter and W., Hunter, J (1988) Estadística para investigadores. Introducción al diseño de experimentos, análisis de datos y construcción de modelos - Barcelona:Editorial Reverté.
Cochran, W.G. and Cox, G.M. (1957) Experimental Designs - second. ed, New York: John Wiley & Sons, Inc.
Fisher, R.A. (1925) Statistical Methods for Research Workers - Edinburgh: Oliver & Boyd.
Snedecor, G.W. and Cochran, W.G. (1980) Statistical Methods - seventh ed, IA: Iowa State University Press.
MODELS FOR CATEGORICAL DATA
Agresti, A. (1990) Categorical Data Analysis - New York: John Wiley & Sons, Inc.
Andersen, P.K. and Borgan, O. (2000) Statistical Models BAsed on Counting Processes - Springer-Verlag New York, Inc.
Cox, D.R. and Snell, E.J. (1989) The Analysis of Binary Data - second ed, London: Chapman and Hall.
MODELS OF REGRESSION
Amemiya, T. (1985) Advanced Econometrics - Oxford Basil Blackwell
Draper, N. and Smith, H. (1981) Applied Regression Analysis - second ed, New York: John Wiley & Sons, Inc.
Jobson, J.D. (1991) Applied Multivariate Data Analysis (Volume I: Regression and Experimental Design) - Springer-Verlag New York, Inc.
Rao, C.R. (1973) Linear Statistical Inference and Its Applications - second ed, New York: John Wiley & Sons, Inc.
LOGÍSTIC REGRESSION
Agresti, A. (1984) Analysis of Ordinal Categorical Data - New York: John Wiley & Sons, Inc.
Christensen, R. (1990) Log-Linear Models - Springer-Verlag New York, Inc.
Hosmer, D.W, Jr and Lemeshow, S. (1989) Applied Logistic Regression - John Wiley & Sons, Inc.
GENERALIZED LINEAR MODELS
McCullagh, P. and Nelder, J.A. (1989) Generalized Linear Models - London: Chapman and Hall.
Rao, C.R. (1973) Linear Statistical Inference and Its Applications - New York: John Wiley & Sons, Inc.
MULTIVARIANT ANALYSIS
Escofier, B. and Pagès, J. (1988) Análisis factoriales simples y múltiples: obejtivos, métodos e interpretación - Servicio editorial de la Universidad del País Vasco.
Greenacre, M.J. (1984) Theory and Applications of Correspondence Analysis - London: Academic Press.
Lebart, L., Morineau, A. and Warwick, K.M. (1984) Multivariate Descriptive Statistical Analysis: Correspondence Analysis and Related Techniques for Large Matrices - New York: John Wiley & Sons, Inc.
DISCRIMINANT ANALYSIS
Hand, D.J. (1981) Discrimination and Classification - New York: John Wiley & Sons, Inc.
Lachenbruch, P.A. (1975) Discriminant Analysis - New York: Hafner.
ANALYSIS OF CONGLOMERATES
Duran, B.S. and Odell, P.L. (1974) Cluster Analysis - New York: Springer-Verlag.
Everitt, B.S. (1980) Cluster Analysis - second ed, London: Heineman Educational Books Ltd.
Hartigan, J.A. (1975) Clustering Algorithms - New York: John Wiley & Sons, Inc.
SURVIVABILITY ANALYSIS
Collet, D. (1994) Modelling survivaldata in medical research - Chapman & Hall.
Cox, D.R. and Oakes, D. (1984) Analysis of Survival Data - London: Chapman and Hall.
Kalbfleisch, J.D. and Prentice, R.L. (1980) The Statistical Analysis of Failure Time Data - New York: John Wiley & Sons, Inc.
Klein, J. and Moeschberger, M. (1997) Survival Analysis: Techniques for censored and truncated data - New York: Springer
Lawless, J.E. (1982) Statistical Models and Methods for Lifetime Data - New York: John Wiley & Sons,Inc.
STATISTICAL SAMPLE
Kish, L. (1965) Survey Sampling - New York: John Wiley & Sons, Inc.
Wolter, K. M. (1985) Introduction to Variance Estimation - New York: Springer-Verlag Inc.
NON PARAMETRIC ANALYSIS
Conover, W.J. (1980) Practical Nonparametric Statistics - second ed, New York: John Wiley & Sons, Inc.
Hollander, M. and Wolfe, D.A. (1973) Nonparametric Statistical Methods - New York: John Wiley & Sons, Inc.
STRUCTURAL EQUATIONS
Bollen, K.A. (1989) Structural Equations with Latent Variables - New York: John Wiley & Sons, Inc.
Wiley, D.E. (1973) The Identification Problem for Structural Equation Models with Unmeasured Variables in Goldberger A.S. and Duncan, O.D. eds. Tructural Equation Models in the Social Sciences - New York: Academic Press.
Time Series Analysis
Fuller, W.A. (1976) Introduction to Statistical Time Series - New York: John Wiley & Sons, Inc.
MIXED MODELS
Littell, R.C., Milliken, G.A., Stroup, W.W., and Wolfinger, R.D. (1996) SAS System for Mixed Models - Cary, NC: SAS Institute Inc.
Verbeke, G. and Molenberghs, G. (1997) Linear Mixed Models in Practice: A SAS-Oriented Approach - New York: Springer.
BOOTSTRAP
Good, P. (2000) Permutation Tests: A practical guide to resampling methods for testing hypotheses - Springer Verlag New York, Inc.
DATAMINING
Hastie, T. and Tibshirani, R. (2001) The Elements of Statistical Learning: data mining, inference and prediction - Springer- Verlag New York, Inc
The software required for the TFG.