Προβολή πηγαίου κώδικα για τη σελίδα Non Parametric Statistics - Categorical Data Analysis (MAE835)

* [[Μη Παραμετρική Στατιστική - Κατηγορικά Δεδομένα (ΜΑΕ835)|Ελληνική Έκδοση]]
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=== General ===
{| class="wikitable"
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! School
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School of Science
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! Academic Unit
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Department of Mathematics
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! Level of Studies
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Undergraduate
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! Course Code
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ΜΑΕ835
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! Semester
|
8
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! Course Title
|
Non Parametric Statistics- Categorical Data Analysis
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! Independent Teaching Activities
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Lectures (Weekly Teaching Hours: 3, Credits: 6)
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! Course Type
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Special Background
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! Prerequisite Courses
| -
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! Language of Instruction and Examinations
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Greek
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! Is the Course Offered to Erasmus Students
|
Yes (in English, reading Course)
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! Course Website (URL)
| See [https://ecourse.uoi.gr/ eCourse], the Learning Management System maintained by the University of Ioannina.
|}

=== Learning Outcomes ===
{| class="wikitable"
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! Learning outcomes
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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. 
|-
! General Competences
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* Working independently 
* Decision-making
* Production of free, creative and inductive thinking
* Criticism and self-criticism.
|}
=== Syllabus ===
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 ===
{| class="wikitable"
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! Delivery
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Classroom (face-to-face)
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! Use of Information and Communications Technology
| -
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! Teaching Methods
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{| class="wikitable"
! Activity
! Semester Workload
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| Lectures (13X3)
| 39
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| Working independently
| 78
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| Exercises-Homeworks
| 33
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| Course total 
| 150
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! Student Performance Evaluation
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Final written exam in Greek (in case of Erasmus students in English). 
|}
=== Attached Bibliography ===

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See the official [https://service.eudoxus.gr/public/departments#20 Eudoxus site] or the [https://cloud.math.uoi.gr/index.php/s/62t8WPCwEXJK7oL local repository] of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:

{{MAE835-Biblio}}