Statistical Data Analysis (MAE832)

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General

School

School of Science

Academic Unit

Department of Mathematics

Level of Studies

Undergraduate

Course Code

ΜΑΕ832

Semester

8

Course Title

Statistical Data Analysis

Independent Teaching Activities

Lectures-Laboratory (Weekly Teaching Hours: 3, Credits: 6)

Course Type

Special background

Prerequisite Courses -
Language of Instruction and Examinations

Greek

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.

Learning Outcomes

Learning outcomes

In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R). Emphasis is placed on choosing the appropriate statistical methodology and examining whether the assumptions of its application are met.

General Competences
  • Working independently
  • Decision-making
  • Production of free, creative and inductive thinking
  • Criticism and self-criticism.

Syllabus

In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R).

Upon completion of the course, the student will be able to:

  1. enter data into the computer
  2. conduct descriptive statistical analysis, that is to summarize the available data,
  3. conduct basic data analyzes (testing hypotheses concerning the mean of a population, the means of two populations with dependent and independent samples, one way analysis of variance etc.,)
  4. fits simple-multiple linear regression models, binomial logistic regression models, checking whether the assumptions of their application are violated
  5. applies basic methodologies of multidimensional analysis (clustering, factor analysis)
  6. present the results of the above analyzes (reference report).

Teaching and Learning Methods - Evaluation

Delivery

Classroom (face-to-face)

Use of Information and Communications Technology Use of ICT in communication with students
Teaching Methods
Activity Semester Workload
Lectures 39
Working independently 78
Exercises-Homeworks 33
Course total 150
Student Performance Evaluation

Final written exam in Greek (in case of Erasmus students in English) which concentrates on the solution of problems which are motivated by the main themes of the course.

Attached Bibliography

See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:

  • Andy Field. Η Διερεύνηση της Στατιστικής με τη χρήση του SPSS της IBM. Εκδόσεις Προπομπός
  • Julie Pallant. SPSS Οδηγός ανάλυσης δεδομένων με το ΙΒΜ SPSS. Εκδόσεις Κλειδάριθμος ΕΠΕ.
  • Δ. Φουσκάκης. Ανάλυση Δεδομένων με χρήση της R. Εκδόσεις Τσότρας Αν. Αθανάσιος
  • Joaquim P. Marques de Sá. Applied Statistics Using SPSS, STATISTICA, MATLAB and R. Springer Berlin Heidelberg Διαθέτης (Εκδότης) HEAL-Link Springer ebooks
  • Μαλεφάκη, Σ., Μπατσίδης, Α., & Οικονόμου, Π. (2023). Στατιστική Ανάλυση Δεδομένων [Προπτυχιακό εγχειρίδιο]. Κάλλιπος, Ανοικτές Ακαδημαϊκές Εκδόσεις.