COURSE UNIT TITLE

: COMPUTER APPLIED STATISTICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
SBE 6068 COMPUTER APPLIED STATISTICS ELECTIVE 1 2 0 6

Offered By

The Institute Of Health Sciences

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

Offered to

Public Health
Pediatric Nursing
Audiology
Psychiatric Nursing
COMMUNITY HEALTH NURSING
Laboratory Animal Science
Occupational Health
Medical Education
Canser Epidemiology Doctorate
Cardiopulmonary Physiotherapy and Rehabilitation PhD Program
Anatomy
Internal Medicine Nursing
Physical Therapy and Rehabilitation
Molecular Pathology
Perfusion Techniques
Basic Oncology
Exercise Physiology
Toxicology
Physical Education and Sport Doctoral
Biochemistry
Biomechanics
Canser Epidemiology
Histology and Embryology
Medical Biology and Genetics
Basic Oncology
Biophysics
Medical Physics
Fundamentals of Nursing
Physiology
Musculoskeletal Tissue Engineering
Translational Oncology
Oncology Nursing
Medical Parasitology
Microbiology
Pharmacology
Surgical Nursing
Nursing Management
Basic Neuroscience
Molecular Medicine
Translational Oncology
Molecular Medicine
Physical Therapy and Rehabilitation
Obstetrics and Gynaecology Nursing

Course Objective

The aim of this course is to teach biostatistical methods that are used in planning, conducting and analysing of the scientific research by using statistical softwares

Learning Outcomes of the Course Unit

1   Preparing data base, checking the data bas efor mistakes and data cleaning
2   Calculating and interpreting descriptive statistics
3   Testing hypothesis and interpreting the results
4   Interpreting the results of lineer regression and logistic regression analysis
5   Estimating sample size and carrying out power analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction Basic concepts in biostatistics
2 Introduction to SPSS package
3 Preparing data base- data base cleaning
4 Descriptive statistics
5 Hypothesis testing
6 Chi square test application and interpretation
7 T tests
8 Mann Whitney U test Wilcoxon signed rank test
9 Correlation and Linear regression
10 Analysis of Variance (ANOVA)
11 Multivariate analysis and modelling methods
12 Mulipl regression
13 Logistic regression
14 Sample size

Recomended or Required Reading

1. K. Özdamar. SPSS ile Biyoistatistik. Kaan Kitabevi, Eskişehir, 2003.
2. Aksakoğlu G. Sağlıkta araştırma teknikleri ve analiz yöntemleri. DEÜ Rektörlük
Matbaası, Izmir 2001.
3. http://www.spss.com.tr/
4.http://www.pitzer.edu/offices/information_technology/documentation/miscellaneous/spssbasics. pdf
5. http://kerem.koseoglu.info/down/spss_manual_v5_(kk).pdf

Planned Learning Activities and Teaching Methods

Interactive presentation take 33% of the course duration.Rest of the time is spent with practicals using teaching guidelines and data bases. Homeworks will be given after each lecture and feedback will be provided to each student.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE ASG * 0.50+ FIN* 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.50+ RST* 0.50


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

Further Notes About Assessment Methods

None

Assessment Criteria

If the average of homework score and final exam score is over 75 then the student will pass the course.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Belgin Ünal, belgin.unal@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 15 1 15
Tutorials 30 1 30
Preparations before/after weekly lectures 15 2 30
Preparation for final exam 1 20 20
Preparing assignments 15 3 45
Preparing presentations 1 8 8
Final 1 2 2
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.12222222222
LO.22222222222
LO.32222222222
LO.42222222222
LO.52222222222