EDT5012 Statistical Data AnalysisBahçeşehir UniversityDegree Programs SOFTWARE ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
SOFTWARE ENGINEERING
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) Be able to specify functional and non-functional attributes of software projects, processes and products.
2) Be able to design software architecture, components, interfaces and subcomponents of a system for complex engineering problems.
3) Be able to develop a complex software system with in terms of code development, verification, testing and debugging.
4) Be able to verify software by testing its program behavior through expected results for a complex engineering problem.
5) Be able to maintain a complex software system due to working environment changes, new user demands and software errors that occur during operation.
6) Be able to monitor and control changes in the complex software system, to integrate the software with other systems, and to plan and manage new releases systematically.
7) Be able to identify, evaluate, measure, manage and apply complex software system life cycle processes in software development by working within and interdisciplinary teams.
8) Be able to use various tools and methods to collect software requirements, design, develop, test and maintain software under realistic constraints and conditions in complex engineering problems.
9) Be able to define basic quality metrics, apply software life cycle processes, measure software quality, identify quality model characteristics, apply standards and be able to use them to analyze, design, develop, verify and test complex software system.
10) Be able to gain technical information about other disciplines such as sustainable development that have common boundaries with software engineering such as mathematics, science, computer engineering, industrial engineering, systems engineering, economics, management and be able to create innovative ideas in entrepreneurship activities.
11) Be able to grasp software engineering culture and concept of ethics and have the basic information of applying them in the software engineering and learn and successfully apply necessary technical skills through professional life.
12) Be able to write active reports using foreign languages and Turkish, understand written reports, prepare design and production reports, make effective presentations, give clear and understandable instructions.
13) Be able to have knowledge about the effects of engineering applications on health, environment and security in universal and societal dimensions and the problems of engineering in the era and the legal consequences of engineering solutions.