PUBLIC RELATIONS AND PUBLICITY
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	Spring 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 prepare the students to become communication professionals by focusing on strategic thinking, professional writing, ethical practice and innovative use of traditional and new media
2)	To be able to create effective public relations plans using fundamental planning components that include situation analysis, public profile, objectives, strategies and tactics.
3)	To be able to apply theoretical concepts related to mass communication, consumer behavior, psychology, persuasion,sociology, marketing, and other related fields to understand how public realtions works.
4)	To be able to have the ability to explain and identify problems associated with the relationships between events and facts in the areas of public relations, persuasive communication, communication management, corporate communications.
5)	To be able to analyze primary and secondary research data in the fields of perception and reputation management and corporate communication practices.
6)	To be able to search, write, and design articles, newsletters, and fliers, brochures, and announcements, in styles and formats appropraite various audiences, mediums and settings.
7)	To be able to apply the underlying theories of communication and the necessities of work safety to different types of public relations processes and campaigns.
8)	To be able to develop creative and persuasive management skills in terms of reputation, employee relations, leadership and similar corporate practices.
9)	To be able to take responsibility in an individual capacity or as a team in generating solutions to given scenarios which can occur in public relations processes.
10)	To be able to understand how an organizational culture works and how employees and leaders create messages as a communication tool.
11)	To be able to critically discuss and interpret theories, concepts, methods, tools and ideas in the field of public relations.
12)	To be able to to use information, communication technologies and computer software with the required level of public relations, marketing communication, persuasive communication, communication management, corporate communications.
13)	To be able to explain and describe business marketing activities, economics, business law and global business practices.
14)	To be able to recognize national and international, social and cultural dimensions of public relations.