Learning objectives
ACQUISITION OF COMPETENCES FOR DESIGNING AND ANALYSING, IN STATISTICAL TERMS, QUANTITATIVE SETS OF DATA RESULTING FROM EXPERIMENTS IN NATURAL ENVIRONMENTS. ABILITY TO ANALYSE SETS OF ECOLOGICAL-ENVIRONMENTAL DATA USING MULTIVARIATE STATISTICAL MODELS
Prerequisites
Knowledge of basic univariate statistics is necessary.
Course unit content
1. Review of Matrix Algebra: definitions, addition, subtraction between matrices; multiplication and inversion of matrices, etc. <br />
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2. Multiple Regression: general information on the method, calculation examples, verification of the degree of fit of the model, etc. <br />
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Calculation examples with application to the environmental field. <br />
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3. Analysis of Multiple Covariance via Multiple Regression. Methodology with calculation examples. <br />
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Examples of application to Environmental Sciences. <br />
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4. Principal Component Analysis: theory with component calculation examples. <br />
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Characterization of components and their interpretation. <br />
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Examples of application to Environmental Sciences. <br />
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5. Normal Multivariate Distribution: main statistical/sampling characteristics. <br />
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Multivariate significance test: general details and references to univariates; <br />
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Tests on 1 multivariate sample; <br />
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Tests on 2 multivariate samples; <br />
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Tests on K multivariate samples: (K>2); <br />
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6. Discriminant Analysis: theory and calculation of discriminant functions and their characterization. <br />
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7. Canonical Correlation Analysis: theory with examples of calculation of canonical correlations. Characterization of correlations and their interpretation. <br />
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Examples of application in the environmental field. <br />
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8. Multivariate Analysis of Variance: general details with references to the univariate case. <br />
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The case of 1 classification criterion. Calculation examples with application to environmental research. <br />
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9. Multivariate Analysis of Variance. <br />
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The case of 2 classification criteria. Interaction: calculation and its interpretation. <br />
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Examples of application to the environmental field. <br />
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10. Multivariate Classification Techniques: general details. <br />
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Hierarchical clustering methods. Other methods. <br />
Examples of hierarchical clustering in analysis of the territory. <br />
Full programme
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Bibliography
Professor's lecture notes. <br />
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B. Tabachnick & L. Fidel, 2001. Using multivariate statistics. Allyng & Bacon, Boston. <br />
Teaching methods
The course will be conducted through classroom lectures by the professor and will include a written and oral test.
Assessment methods and criteria
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Other information
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