Statistical Data Analysis (MAE832)

Undergraduate Courses Outlines - Department of Mathematics

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)	http://users.uoi.gr/abatsidis/832.html

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: enter data on the computer conduct descriptive statistical analysis that summarizes the available data perform basic data analysis (testing for outliers and normality, basic hypothesis testing with dependent and independent samples, one way anova) adjust linear models, mainly simple regression, controlling on whether the assumptions of the model are violated or not 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.

Syllabus

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

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 Eudoxus. Additionally:

• 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).