| Center |
| Faculty of Mathematics |
| Departament |
| Statistics and Operational Research |
| Lecturers in charge |
| Sin datos cargados |
| Met. Docent |
| In the classes of theory one presents a problem with a clear aim. One discusses and explains the proposed solutions. In the practical classes the solutions are implemented by statistical programs and are applied to real data. |
| Met. Avaluació |
| The first modular exam will be realized in February. In the final examination of June it will be possible eliminate the matter overcome in the first partial one. The examinations will have a theoretical - practical character with computer. The personal works presented in class will be valued. |
| Bibliografia |
| COCHRAN, W (1977) Sampling techniques.3ed. New York: Wiley. EVERITT, B. S. & DUNN, G. (1991) Applied Multivariate Data Analysis. New York: Wiley. HEDAYAT, A.S. & SINHA, B.K. (1991) Design and Inference in Finite Population Sampling. New York. Wiley. PEÑA, D. (2002) Análisis de datos Multivariantes. Madrid McGraw-Hill. SÄRNDAL, SWENSSON & WRETMAN (1992) Model assisted survey sampling. Springer-Verlag. SEBER, G.A.F. (1984) Multivariate Observations. New York: Wiley TRYFOS, P. (1996) Sampling Methods for Applied Research. New York: Wiley |
| Continguts |
| Initial examination of multivariate data. Graphical characteristics and representations. Transformations and detection of atypical data. Pincipal Components Analysis. Definition and properties. Election of the number of components. Analysis of Canonical Correlations. Obtaining and invarianza of the canonical variables. Canonical analysis of populations. Optimality of the canonical representation. Multidimensional.Scaling Calculation of the Principal Coordinates. Nonmetric Escalamiento. Simple and multiple Correspondences Analysis. Absolute and relative contributions. Cluster Analysis. Classification in k groups. Hierarchic classification. Other classifications. Probability designs. Properties. Parameters and estimators. Simple random samplings and allies. Systematic sampling. Poisson Sampling. PIPS Sampling. Sampling with replacement PPS. Stratified sampling. Sampling by Multi-stage Cluster and. Sampling with replacement in some stage. More complex Estimators problems than the total. Effect of bias. The Taylor linearization technique of variance estimation. |
| Objetius |
| Immediate goal that we will approach is the multivariant analysis of data with descriptive techniques, basing to us on geometric concepts and optimization of very clear functions objective. The second objective will be to prepare the student to design and to analyze surveys. For it we will study of theoretical form the main techniques of sampling to actually base the advantages and disadvantages of the election of the type of sampling. |
| URL de Fitxa |