Graduate Education Institute · Islamic Economics and Finance (English) · Master
Course Objective
This course is designed to introduce students to multivariate data analysis techniques and their applications in in various field of Islamic Economics and Finance, business administration and political sciences . The course contents would cover statistical techniques related to group comparisons, such as T-test, ANOVA, Chi-sqaure, etc., as well as techniques related to relationship exploration, such as EFA, Regression Analysis, Cluster Analysis, etc. Furthermore, this course would also expose students to the appropriate ways of reporting statistical results in research paper and dissertation.
Course Content
This is a practical course on scholarly methods designed to enable students to carry out their own research projects. The emphasis is on quantitative research methods. Topics covered include the philosophy of research. The course also focuses on the ethics of carrying out primary and secondary research. This course is designed to: a) describe the key components of social research, b) develop skills and knowledge about quantitative social research, and c) identify criteria used to evaluate the quality of social research.
Rules
Academic Integrity: Students are expected to adhere to the ethical code of Istanbul Sabahattin Zaim University, and you commit to these principles by enrolling in this class. Academic dishonesty in any form is unacceptable, and penalties range from failing the exam to being dismissed from the university. We consider any violation of academic integrity to be a very serious matter.
Classroom Behavior:
- Everyone is strongly encouraged to ask questions and make comments during the class.
- Please turn off cell phones and other devices unless required by the lecturer.
- Please arrive on-time and expect to leave at the end of class.
Course Learning Outcomes
- Demonstrate high level of responsibility and autonomy as a quantitative data analyst.
- Recognizing and describing the important “group” and “relationship exploration” related statistical techniques.
- Demonstration of ability to interpret statistical findings reported in top quality quantitative and qualitative research journals.
- Choose, adapt, and develop a research questionnaire/tool.
- Apply advanced quantitative data analysis techniques using latest statistical software(s)
- Demonstrate ability to report empirical findings adequately using IT tools.
- Apply advanced numerical skills to conduct the research in the field of specialization
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 15 | 3 | 45 |
| Out of Class Study Period | 15 | 3 | 45 |
| Midterm | 1 | 25 | 25 |
| Quiz | 0 | 0 | 0 |
| Assignment | 1 | 40 | 40 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 20 | 20 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Introduction to research • What is Research? • Structure of Research • Research Philosophy • Basic And Applied Research | - |
| 2 | The Research (Design) Process I • Issues of precision and confidence in determining sample size • Precision and confidence: trade-offs • Sample data and hypothesis testing • Sample size • Efficiency in sampling • Sampling in qualitative studies | - |
| 3 | The Research (Design) Process II • Issues of precision and confidence in determining sample size • Precision and confidence: trade-offs • Sample data and hypothesis testing • Sample size • Efficiency in sampling • Sampling in qualitative studies | - |
| 4 | Data, Probability and Sampling • Population, element, population frame, sample, subject • Reasons for sampling • Representativeness of the sample • Sampling in cross cultural research • Issues of precision and confidence in determining sample size • Precision and confidence: trade-offs • Sample data and hypothesis testing • Sampling in qualitative studies | - |
| 5 | Querstionnaire development Variable construction Item Development | - |
| 6 | Confidence Interval Confidence Intervals for the Mean Confidence Intervals for Variances and Standard Deviations | - |
| 7 | Hypothesis Testing z Test for a Mean t Test for a Mean | - |
| 8 | Hypothesis Testing Chi square Test for a Variance or Standard Deviation | - |
| 9 | Presnetation of reseearch proposals | Presnetation of reseearch proposals |
| 10 | Getting started • Creating a data file and entering data • Screening & cleaning data • Descriptive statics • Exploring the data • Choosing appropriate statistical technique | - |
| 11 | Coding Research Items and Construction of variables Scale’s reliability & validity • Introduction to scale’s reliability & validity • Calculating composite reliability using SPSS | - |
| 12 | Basic tests Intedendent t-test; Paired t-test; ANOVA test; Two-way ANOVA; | - |
| 13 | Exploratory Factor Analysis (EFA) • Steps involved in EFA • Procedure for EFA • Interpretation of output of EFA produced in SPSS • Reporting results of EFA in a research paper | - |
| 14 | Correlation analysis; Non-parametric statistics • Chi-square • Mann-Whitney U Test • Wilcoxon Signed Rank Test • Kruskal-Wallis Test • Friedman Test | - |
| 15 | Multiple, regression analysis • Purpose & assumptions of each type of regressions, i.e., multiple & logistic regressions. • Multiple regression (standard & hierarchical multiple regression) • Logistic regression • Interpretation of output of each of the above mentioned regression type produced in SPSS • Reporting results of each of the above mentioned regression type in a research paper | - |
| 16 | Final Exam | Final Exam |