Data Analysis and Statistical Packages (ΣΕΕ5)

• Ελληνική Έκδοση
• Graduate Courses Outlines
• Department of Mathematics

General

School	School of Science
Academic Unit	Department of Mathematics
Level of Studies	Graduate
Course Code	ΣΣΕ5
Semester	2
Course Title	Data Analysis and Statistical Packages
Independent Teaching Activities	Lectures (Weekly Teaching Hours: 3, Credits: 7.5)
Course Type	Specialised general knowledge
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	The students should be able to understand which statistical method is appropriate for each problem under study and to confirm that the relative assumptions hold. Moreover, the student should be able to 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

Descriptive Statistics. Review of basic undergraduate concepts like t-test, Mann Whitney test etc. Multiple Regression and Diagnostics. One Way and Two Way Analysis of Variance. Introduction to Logistic Regression. Repeated Measures Analysis. Reliability and Factor Analysis. Introduction to Survival Analysis: Roc curves, Cox PH Regression Model.

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 - Homework 70.5 Course total 187.5
Student Performance Evaluation	Final written exam in Greek (in case of Erasmus students in English) which includes analysis of real data sets.

Attached Bibliography

• Barnett, V. and Lewis, T. (1978). Outliers in statistical data. Wiley, New York.
• Belsley, David A, Kuh, Edwin and Welsch, Roy E. (1980). Regression diagnostics: identifying influential data and sources of collinearity. Wiley Series in Probability and Mathematical Statistics. John Wiley & Sons.
• Samprit Chatterjee, Ali S. Hadi (2012). Regression analysis by examples. John Wiley & Sons, Inc.
• Coakes, S. and Steed, L ( 1999). S.P.S.S. Analysis without Anguish. Wiley.
• Field, A. P. (2005). Discovering statistics using S.P.S.S. (Second Edition). London: Sage.
• Landau, S. and Everitt (2004). A Handbook of Statistical Analyses using S.P.S.S.. Chapman and Hall.
• Neter, J., Kutner, M., Nachtsheim, C. and Wassserman, W. (1996). Applied linear statistical models. 4th Edition, Irwin, Inc.
• Rawlings, J. O. (1988). Applied regression analysis: a research tool. Wadsworth & Brooks/Cole Advanced Books & Software, Pacific Grove, CA.
• Rencher, A. C. (2000). Linear Models in Statistics. Wiley.
• Searle, S. R. (1971). Linear models. John Wiley & Sons, Inc.
• Seber, G. A. F. (1977). Linear regression analysis. John Wiley & Sons.