NURSING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EEE5022	Applied Statistics	Fall	3	0	3	9

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assoc. Prof. SAEID KARAMZADEH
Course Lecturer(s):	Prof. Dr. SELİM ZAİM
Recommended Optional Program Components:	none..........
Course Objectives:	The course introduces fundamental topics in statistics and implements its applications to industrial, medical, financial, energy and similar type very large-size datasets to infer meaninful statistical results. The course is for gradute students with no significant background on this subject. Implementations will be performed on the open source statistical software R. Introduction to R programming will be given.

Learning Outcomes

The students who have succeeded in this course;
I. Identify basic terms in statistics.
II. Gain ability to use and apply basic methods and programming tools used in statistics over various engineering disciplines.
III. Ability to explore data and its relationships.
IV. Ability to perform hypothesis testing for statistical problems.
V. Perform statistical inference over statistical data.

Course Content

Topics include: Introduction to R programming, Sampling, Data Exploration, Exploring Relationships, Probability, Random Variables and Probability Distributions, Estimation, Hypothesis Testing, Statistical Inference, Multiple Testing Correction, ANOVA, Analysis of Categorical Variables, Regression Analysis, Bayesian Analysis, Survival Analysis, Over Representation Analysis, Meta Analysis.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction
2)	Introduction to R statistical programming
3)	Term Project
4)	Data Exploration with R
5)	Visualizing and Summarizing Relationships
6)	Probability and Random Variables
7)	Estimation in datasets
8)	Hypothesis Testing for various engineering applications
9)	Statistical Inference over various large datasets
10)	ANOVA
11)	Analysis of Categorical Variables
12)	Regression and Bayesian Analysis
13)	Survival analysis
14)	Over Representation Analysis

Sources

Course Notes / Textbooks:	Principles of Applied Statistics (Paperback), by D. R. Cox, Christl A. Donnelly 2011 ISBN-10: 1107644453 \| ISBN-13: 978-1107644458
References:	Introductory Statistics with R Peter Dalgaard 2011 ISBN 978-0-387-79053-4

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Project	1	% 30
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 30
PERCENTAGE OF FINAL WORK		% 70
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Study Hours Out of Class	14	42
Project	1	30
Midterms	1	40
Final	1	50
Total Workload		204

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	"To plan and assess nursing care within a holistic approach, in accordance with theoretical and evidence-based practices. "
2)	To act in accordance with ethical principles and values in Nursing practices.
3)	To use life-long learning, problem-solving and critical thinking skills.
4)	To use Nursing models/theories in health promotion, protection and care.
5)	To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach.
6)	"To have skills for training and consulting according to health education needs of individual, family and the community. "
7)	"To be sensitive to health problems of the community and and to able to offer solutions. "
8)	"To be able to use interpersonal and intercultural communication skills effectively in Nursing pratices. "
9)	"To be able to use healthcare/information technologies in Nursing practice and research. "
10)	To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively.
11)	To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level.
12)	To take responsibility and lead in events in order to contribute to health services and Nursing profession.