GASTRONOMY AND CULINARY ARTS (TURKISH)
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
EDT5012	Statistical Data Analysis	Fall	3	0	3	8

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 :	Prof. Dr. ALİ BAYKAL
Course Lecturer(s):	Prof. Dr. HASAN KEMAL SUHER Assoc. Prof. MEHMET SENCER ÇORLU Prof. Dr. ALİ BAYKAL Dr. Öğr. Üyesi GURSU ASIK
Recommended Optional Program Components:	NONE
Course Objectives:	This course will primarily focus on quantitative data analysis. Topics in this course will include descriptive statistics, hypothesis testing, sampling distributions, t-test, ANOVA, and regression. A parallel learning activity will be to learn how to use SPSS (Statistical Package for the Social Sciences) to run the above-mentioned statistical procedures.

Learning Outcomes

The students who have succeeded in this course;
At the end of this course, students will;
o Develop an understanding of the connection between quantitative research types and corresponding statistical analysis types.
o Develop a knowledge base for basic statistical concepts, terms, and principles.
o Develop knowledge of introductory level statistical methods.
o Develop skills to perform statistical analysis for given research types.
o Develop skills to use statistical software to analyze quantitative data.
o Develop knowledge and skills to report quantitative data analysis results.

Course Content

Descriptive statistics; hypothesis testing; sampling distributions; t-test; ANOVA; regression; running these analyses in SPSS and interpreting the output; writing up quantitative data analysis results

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to statistical methods	NONE
2)	Descriptive statistics	Ch. 1 and 2: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 1, 2, and 3: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
3)	Descriptive statistics	Ch. 1 and 2: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 1, 2, and 3: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
4)	Normal distribution	Ch. 3: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 1, 2, and 3: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
5)	Normal distribution	Ch. 3: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 1, 2, and 3: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
6)	Sampling distribution and basic hypothesis testing	Ch. 4: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth.
7)	Sampling distribution and basic hypothesis testing	Ch. 4: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth.
8)	Mean comparison of two groups	Ch. 7: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 9: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
9)	Mean comparison of two groups	Ch. 7: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 9: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
10)	Mean comparison of three or more groups	Ch. 11: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 10: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
11)	Mean comparison of three or more groups	Ch. 11: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 10: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
12)	Simple regression	Ch. 9 and 15: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 7: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
13)	Simple regression	Ch. 9 and 15: Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth. Ch. 7: Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.
14)	Writing up data analysis results	NONE

Sources

Course Notes / Textbooks:	Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage. Howell, D.C. (2007). Statistical methods for psychology (6th ed.).Belmont, CA: Thomson Wadsworth.
References:	Cozby, P.C. (2007). Methods in behavioral research (9th ed.). Boston: McGraw Hill. Pedhazur, E.J. & Schmelkin, L.P. (1991). Measurement, design, and analysis: An integrated approach. Hillsdale, NJ: Lawrence Erlbaum Associates. Salkind, N.J. (2004). Statistics for people who (think they) hate statistics (2nd ed.). London: Sage.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	1	% 20
Midterms	2	% 40
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	7	98
Midterms	2	15	30
Final	1	20	20
Total Workload			190

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)	- Possess advanced level theoretical and practical knowledge supported by textbooks with updated information, practice equipments and other resources.	2
2)	Use of advanced theoretical and practical knowledge within the field. -Interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the field.	4
3)	Inform people and institutions, transfer ideas and solution proposals to problems in written and orally on issues in the field. - Share the ideas and solution proposals to problems on issues in the field with professionals and non-professionals by the support of qualitative and quantitative data. -Organize and implement project and activities for social environment with a sense of social responsibility. -Monitor the developments in the field and communicate with peers by using a foreign language at least at a level of European Language Portfolio B1 General Level. -Use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge.	5
4)	Evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach. -Determine learning needs and direct the learning. -Develop positive attitude towards lifelong learning.	3
5)	Act in accordance with social, scientific, cultural and ethic values on the stages of gathering, implementation and release of the results of data related to the field. - Possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also, environmental protection, worker's health and security.	3
6)	Conduct studies at an advanced level in the field independently. - Take responsibility both as a team member and individually in order to solve unexpected complex problems faced within the implementations in the field. - Planning and managing activities towards the development of subordinates in the framework of a project	3