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School of Science
Department of Mathematics
|Level of Studies||
Non Parametric Statistics- Categorical Data Analysis
|Independent Teaching Activities||
Lectures (Weekly Teaching Hours: 3, Credits: 6)
|Language of Instruction and Examinations||
|Is the Course Offered to Erasmus Students||
Yes (in English, reading Course)
|Course Website (URL)||See eCourse, the Learning Management System maintained by the University of Ioannina.|
The aim of this course is to introduce students to the methods of Non parametric techniques (goodness-of-fit tests, ranks etc) as well as their application to real practical problems. At the end of the course the student should have understood the basic methods of Non-Parametric Statistics and Categorical Data, knowing when to adopt and how to apply them for analyzing data.
Empirical distribution function, Goodness of fit tests: Kolmogorov-Smirnov test, Chi-square, Runs test, Sign tests, Wilcoxon - Mann - Whitney test, Kruskal - Wallis test. Correlation coefficients. Categorical Variables. Statistical inference for binomial and multinomial parameters, Contingency Tables, Comparing two proportions, Testing: independence, Symmetry, Homogeneity. 2 x 2 Tables (Exact Fisher's test, McNemar's test). Applications. Loglinear models.
Teaching and Learning Methods - Evaluation
|Use of Information and Communications Technology||-|
|Student Performance Evaluation||
Final written exam in Greek (in case of Erasmus students in English).
- Agresti, A. (2007). An Introduction to Categorical Data Analysis. 2 ed. ISBN: 978- 0-470-38800-# Wiley
- Conover, W. J. (1999). Practical Nonparametric Statistics. 3 ed. ISBN: 978-0-471- 16068-# John Wiley & Sons
- Ζωγράφος, Κ. (2009). Κατηγορικά Δεδομένα. Πανεπιστήμιο Ιωαννίνων.
- Μπατσίδης, Α. (2010). Εισαγωγή στη Μη Παραμετρική Στατιστική. Πανεπιστήμιο Ιωαννίνων