EDT5012 Statistical Data AnalysisBahçeşehir UniversityDegree Programs DIGITAL GAME DESIGNGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
DIGITAL GAME DESIGN
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 Spring 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) Comprehend the conceptual importance of the game in the field of communication, ability to implement the player centered application to provide design.
2) Analyze, synthesize, and evaluate information and ideas from various perspectives.
3) Analyze the key elements that make up specific game genres, forms of interactions, mode of narratives and understand how they are employed effectively to create a successful game.
4) Understand game design theories and methods as well as implement them during game development; to make enjoyable, attractive, instructional and immersive according to the target audience.
5) Understand the technology and computational principles involved in developing games and master the use of game engines.
6) Understand the process of creation and use of 2D and 3D assets and animation for video games.
7) Understand and master the theories and methodologies of understanding and measuring player experience and utilize them during game development process.
8) Comprehend and master how ideas, concepts and topics are conveyed via games followed by the utilization of these aspects during the development process.
9) Manage the game design and development process employing complete documentation; following the full game production pipeline via documentation.
10) Understand and employ the structure and work modes of game development teams; comprehend the responsibilities of team members and collaborations between them while utilizing this knowledge in practice.
11) Understand the process of game publishing within industry standards besides development and utilize this knowledge practice.
12) Pitching a video game to developers, publishers, and players; mastering the art of effectively communicating and marketing the features and commercial potential of new ideas, concepts or games.