EDT5012 Statistical Data AnalysisBahçeşehir UniversityDegree Programs ARCHITECTUREGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ARCHITECTURE
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
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) Using the theoretical/conceptual and practical knowledge acquired for architectural design, design activities and research.
2) Identifying, defining and effectively discussing aesthetic, functional and structural requirements for solving design problems using critical thinking methods.
3) Being aware of the diversity of social patterns and user needs, values and behavioral norms, which are important inputs in the formation of the built environment, at local, regional, national and international scales.
4) Gaining knowledge and skills about architectural design methods that are focused on people and society, sensitive to natural and built environment in the field of architecture.
5) Gaining skills to understand the relationship between architecture and other disciplines, to be able to cooperate, to develop comprehensive projects; to take responsibility in independent studies and group work.
6) Giving importance to the protection of natural and cultural values in the design of the built environment by being aware of the responsibilities in terms of human rights and social interests.
7) Giving importance to sustainability in the solution of design problems and the use of natural and artificial resources by considering the social, cultural and environmental issues of architecture.
8) Being able to convey and communicate all kinds of conceptual and practical thoughts related to the field of architecture by using written, verbal and visual media and information technologies.
9) Gaining the ability to understand and use technical information about building technology such as structural systems, building materials, building service systems, construction systems, life safety.
10) Being aware of legal and ethical responsibilities in design and application processes.