QUANTITATIVE DATA ANALYSIS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
SOS369	QUANTITATIVE DATA ANALYSIS	5	3	3	5

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Elective
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	This course aims to help students use statistical programs actively, interpret the results of research in a meaningful way, and gain knowledge and skills in these methods by recognizing statistical methods.
Contents of the Course Unit:	Contents of the course include; introduction of SPSS program, explaining the types of analysis, research design, explaining the types of analysis according to the type of variables, parametric and non-parametric statistics, data entry to SPSS, interpretation of the obtained data.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Knows the SPSS program.
Uses the SPSS program.
Interprets the results of the analysis performed by SPSS, explain the relationship between variables.
Remembers the information about the universe and sample, how to collect the data and how to perform a quantitative analysis and apply it via SPSS.
Analyzes the data by entering SPSS program.
Distinguishes the types of statistics and design a method according to the research.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Introduction to Statistics; basic concepts	Lecture
2	Reading	Introduction to SPSS; Presentation of SPSS menus	Lecture
3	Reading	Research design and Codebook Preparation	Lecture -Demonstration
4	Reading - Practice	Data File Preparation and Introduction to SPSS	Lecture -Demonstration
5	Reading - Practice	Presentation of Preliminary research tests for the reliability of the research; confidence test	Lecture -Demonstration
6	Reading - Practice	Methods used in the interpretation of the relationship between variables; correlation, regression, factor analysis	Lecture -Demonstration
7	Reading - Practice	Methods used in the interpretation of the relationship between variables; correlation, regression, factor analysis	Lecture -Demonstration
8	-	MID-TERM EXAM	-
9	Reading - Practice	Methods used in the comparison of the groups; non-parametric tests	Lecture -Demonstration
10	Reading - Practice	T - test	Lecture -Demonstration
11	Reading - Practice	Variance Analysis I	Lecture -Demonstration
12	Reading - Practice	Variance Analysis II	Lecture -Demonstration
13	Reading - Practice	Graphitising research findings and reporting types	Lecture -Demonstration
14	Reading - Practice	Graphic analysis and interpretation of results	Lecture -Demonstration
15	Reading - Practice	Revision	Lecture -Demonstration
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Can, Abdullah. (2016). SPSS ile bilimsel arastirma surecinde nicel verilerin analizi. Ankara: Pegem Academy Publications
Buyukozturk, S., Cakmak, E. K., Akgün, O. E., Karadeniz, S., & Demirel, F. (2016). Bilimsel arastirma yontemleri. Ankara: Pegem Academy Publications
Koseoglu, M., & Yamak, R. (2011). Uygulamalı istatistik. Trabzon: Derya Bookstore
Treiman, Donald J. (2014). Quantitative data analysis: Doing social research to test ideas. John Wiley & Sons.
Treiman, Donald J. (2014). Quantitative data analysis: Doing social research to test ideas. John Wiley & Sons.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define concepts such as management, manager and leader.
2	Analyze the accuracy, reliability and validity of the new information obtained from the data.

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Report the obtained data.
2	Prepare software and projects related with the field.

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the appropriate resources for data analysis related with the field.
2	Analyze the work processes.

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Manage projects as part of a team.
2	Apply the material, techniques and analyzes in relation with the subject for project and work flows.

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill responsibility with a focus on result in individual and team studies.

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Recognizes what he/she knows about his/her field or not.
2	Act the theoretical knowledge in real life with learning to learn approach.
3	Apply different methods and techniques with an innovative approach in his/her research.

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the results obtained in accordance with voluntarism and social responsibility projects.
2	Establish a healthy contact with colleagues
3	Share the analyzes and obtained results with colleagues.
4	Cooperate with colleagues at international level with the help of foreign language competency.

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Behave in accordance with ethical values regarding the collection, analysis and reporting of data.
2	Participate the design of work processes and systems with full quality.
3	Cooperate with other employees for the continuation of sustainability in the profession.

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	2	26
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	12	4	48
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	1	6	6
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	1	4	4
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	43	0	128