Statistical Data Analysis (MAE832)

Από Wiki Τμήματος Μαθηματικών



School of Science

Academic Unit

Department of Mathematics

Level of Studies


Course Code




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


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

The aim of this course is the implementation of the statistical theory which was developed in "633-Statistical Inference" and "733-Regression and Analysis of Variance" in analyzing (statistical) data by using statistical packages (for instance JMP, SPSS, S-Plus). At the end of the course the student should be able to:

  1. enter data on the computer
  2. conduct descriptive statistical analysis that summarizes the available data
  3. perform basic data analysis (testing for outliers and normality, basic hypothesis testing with dependent and independent samples, one way anova)
  4. adjust linear models, mainly simple regression, controlling on whether the assumptions of the model are violated or not
  5. present and interpret the results of the above analysis.
General Competences
  • Working independently
  • Decision-making
  • Production of free, creative and inductive thinking
  • Criticism and self-criticism.


The implementation of the statistical theory which was developed in "633-Statistical Inference" and "733-Regression and Analysis of Variance" in analyzing data using statistical packages (for instance JMP, SPSS, S-Plus) is the main aim of the course. In particular, the following subjects are discussed: testing hypotheses, simple and multiple linear regression analysis, one way and two way Anova (with and without interaction). The course is laboratorial.

Teaching and Learning Methods - Evaluation


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:

  • Carver and Nash (2006). Doing data analysis with SPSS version #
  • Coakes and Steed (1999).SPSS: Analysis Without Anguish
  • Απόστολος Μπατσίδης (2014). Στατιστική Ανάλυση Δεδομένων με το S.P.S.S. (διαθέσιμες στην ιστοσελίδα του μαθήματος καθώς και διδακτικό υλικό).