COURSE UNIT TITLE

: COMPUTATIONAL STATISTICS AND DATA ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MIF 5016 COMPUTATIONAL STATISTICS AND DATA ANALYSIS ELECTIVE 2 0 0 5

Offered By

Medical Informatics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR PEMBE KESKINOĞLU

Offered to

Medical Informatics

Course Objective

The objective of Computational Statistics & Data Analysis course for the medical informatics students who attend this course is to gain knowledge and practical skills about computational applications of statistics and data analysis. Additionally, this course aims to teach computer and statistics with applications; easily to analyze the data warehouses obtained from researches with the use of computer. It will be interested in MATLAB, SAS, R and statistical software, and to be teached to users basic data analysis and statistical methods especially with the use of MATLAB without theoretical approach.

Learning Outcomes of the Course Unit

1   define basic concepts of statistical data analysis.
2   analyze the data using computer .
3   use various statistical software.
4   apply statistical methods with the use of computer.
5   interpret the results.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to MATLAB for data analysis
2 Programming with MATLAB (m files)
3 R program examples for data analysis
4 Comparison of R, MATLAB and SPSS
5 Using SAS statistical software
6 Create and arrange a data set in MATLAB, R and SAS
7 Random variables, probability and distributions (Discrete and continuous)
8 Explanatory data analysis with MATLAB and R (Exploratory Data Analysis-EDA)
9 MIDTERM
10 Analysis of variance with MATLAB and R
11 Linear Regression Analysis with MATLAB and R
12 Robust Regression with MATLAB
13 Robust Regression with R
14 Applications of Logistic Regression Analysis with SPSS Applications of Logistic Regression Analysis with R
15 Final

Recomended or Required Reading

Textbook(s):
(1) Gentle, J.E., 2002, Elements of Computational Statistics, Springer, ISBN 0387954899.
(2) Martinez, W.L., Martinez, A.R., 2002, Computational Statistics Handbook with MATLAB, Washington D.C., Chapman&Hall/CRC.
(3) Marques De Sa, P.J., 2007, Applied Statistics Using SPSS, Statistica, MATLAB and R, Springer-Verlag, Berlin, Heidelberg.
Supplementary Book(s):
(1) Özdamar, K., 2004, Paket Programlar ile Istatistiksel Veri Analizi I ve II, Kaan Kitabevi.

Planned Learning Activities and Teaching Methods

Presentation/lecturing and interactive discussion.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + PRJ* 0.30 +FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + PRJ* 0.30 +RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homeworks and exams.

Language of Instruction

Turkish

Course Policies and Rules

Attendance is an essential requirement of this course and is the responsibility of the student. Students are expected to attend all lecture and recitation hours. Attendance must be at least 70% for the lectures.

Contact Details for the Lecturer(s)

Dokuz Eylül University, Faculty of Science, Department of Computer Science / Statistics
e-mail: emel.kuruoglu@deu.edu.tr
Tel: 0232 3019510

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparations before/after weekly lectures 13 2 26
Preparation for final exam 1 15 15
Preparing assignments 1 22 22
Preparation for midterm exam 1 15 15
Preparing presentations 1 19 19
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 127

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16
LO.155
LO.245
LO.3555
LO.4545
LO.5