MECHATRONICS (TURKISH)
Associate	TR-NQF-HE: Level 5	QF-EHEA: Short Cycle	EQF-LLL: Level 5

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
EDT5012	Statistical Data Analysis	Spring 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:	Associate (Short 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)	To improve fundamental computer knowledge, to encourage students using office and package programs.
2)	Ability to have and use of fundamental mathematics knowledge and skills the usage of relevant materials.
3)	Ability to recognize general structures of machine equipments and the features of shaping
4)	Ability to grasp manufacturing processes and cutting tool materials, materials, statics, mechanics and fluid science fundemantal knowledge.
5)	Ability to draw assembly and auxilary devices as well as to draw whole or details of a system.
6)	Ability to have a knowledge of fundemantal manufacturing process such as turning, milling, punching,grinding and welding techniques and to have a self esteem in order to work behind the bench.
7)	Ability to do computer aided design and write program on digital benches.
8)	Ability to prepare project report, follow up project process and implement projects.
9)	ability to learn the areas of usage of electronic circuit components. Ability to grasp and write programs for micro controllers and for their components. Ability to design relevant circuits.
10)	Ability to understand the electric motors principles and AC-DC analysis
11)	Ability to gain a dominaion on visual programming
12)	Having the ability to communicate efficiently in verbal and written Turkish, to know at least one foreign language in order to communicate with the colleagues and customers.