Research Methodology(G519)
Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
---|---|---|---|---|---|---|---|
G519 | Research Methodology | 1 | 3 | 0 | 0 | 3 | 7 |
Prerequisites | |
Admission Requirements |
Language of Instruction | Turkish |
Course Type | Compulsory |
Course Level | Masters Degree |
Course Instructor(s) | Zehra Yeşim GÜRBÜZ ygurbuz@gsu.edu.tr (Email) Caner DİNCER cdincer@gsu.edu.tr (Email) Selin PELEK pelekselin@gmail.com (Email) |
Assistant | |
Objective | This course aims to teach the fundamental concepts, principles and applications related with scintific research and methods used. |
Content |
1) Introduction, research project and steps of a research project, basics of sampling. 2) Statistical inference (Estimation of a mean and proportion) 3) Statistical inference (Estimation of a mean and proportion), determination of the sample size. 4) Hypothesis testing, hypothesis, determination of the significance level, type I and II errors, rules of decision. 5) Parametric hypothesis testing (Test of a mean or a proportion of a population). 6) Non-parametric hypothesis testing (Contingency tables, Test Chi-2 of independance, homogeneity and conformity). 7) Non-parametric hypothesis testing. (Test of Kolmogorov-Smirnov, Wilcoxon signed rank test, Mann-Whitney U test) 8) Regression analysis, scatter plots. Regression and correlation analysis and hypothesis. 9) Simple linear regression, computing coefficients using least squares method. Pearson’s coefficient of correlation, tests of regression end correlation coefficients. 10) Multiple regression analysis. Part and partial correlation coefficients. 11) Non-parametric correlation. (Spearman’s rank correlation, coefficient of Kendall-Tau). |
Course Learning Outcomes |
At the end of the course, the studient will be able to : 1. Carry out a scientific research project. 2. Define correctly the population, the sampling method and sample size for a research project. 3. Ascertain the appropriate method for data collection and data analysis. 4. Deduce the right and unbiased outcome as a result of a hypothesis testing. 5. Execute a parametric or non- parametric correlation analysis. |
Teaching and Learning Methods | |
References |
Daniel Wayne W. & Terrell James C., Business Statistics, 5. edition, Houghton Miflin, USA. Newbold, Paul, Statistics for Business and Economics, Pearsons Education Newbold, Paul, İşletme ve İktisat için İstatistik, Çeviren Ümit Şenesen, Literatür Yayıncılık Orhunbilge, Prof. Dr. Neyran, Örnekleme Yöntemleri ve Hipotez Testleri, İ.Ü.İşletme Fak. Yayınları Avcıol Basım Yayın, 2. Baskı, İstanbul 2000. Orhunbilge, Prof. Dr. Neyran, Uygulamalı Regresyon ve Korelasyon Analizi, 2. B., İ.Ü.İşletme Fak. Yayınları, İ.Ü. Basım ve Yayınevi Md., İstanbul 2002 |
Theory Topics
Week | Weekly Contents |
---|---|
1 | Introduction, research project , steps of a research project and basics of sampling. |
2 | Statistical inference (Estimation of a mean and proportion) |
3 | Statistical inference (Estimation of a mean and proportion), determination of the sample size. |
4 | Hypothesis testing, hypothesis, determination of the significance level, type I and II errors, rules of decision. |
5 | Parametric hypothesis testing (Test of a mean or a proportion of a population). |
6 | Parametric hypothesis testing (Test of a mean or a proportion of two populations). |
7 | Mid-term Exam. I |
8 | Non-parametric hypothesis testing (Contingency tables, Test Chi-2 of independance, homogeneity and conformity). |
9 | Non-parametric hypothesis testing. (Test of Kolmogorov-Smirnov, Wilcoxon signed rank test, Mann-Whitney U test) |
Practice Topics
Week | Weekly Contents |
---|
Contribution to Overall Grade
Number | Contribution | |
---|---|---|
Contribution of in-term studies to overall grade | 2 | 50 |
Contribution of final exam to overall grade | 1 | 50 |
Toplam | 3 | 100 |
In-Term Studies
Number | Contribution | |
---|---|---|
Assignments | 0 | 0 |
Presentation | 0 | 0 |
Midterm Examinations (including preparation) | 2 | 50 |
Project | 0 | 0 |
Laboratory | 0 | 0 |
Other Applications | 0 | 0 |
Quiz | 0 | 0 |
Term Paper/ Project | 0 | 0 |
Portfolio Study | 0 | 0 |
Reports | 0 | 0 |
Learning Diary | 0 | 0 |
Thesis/ Project | 0 | 0 |
Seminar | 0 | 0 |
Other | 0 | 0 |
Toplam | 2 | 50 |
No | Program Learning Outcomes | Contribution | ||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||
1 | At the end of the program successful students, Will have a good command of the concepts and theories of different areas of Business Administration such as Production, Marketing, Accounting/Finance, Management and Organizational Behavior and will have an integrative point of view to understand the interaction between these domains. | X | ||||
2 | Will be able to grasp the operation of different functions (Accounting /Finance, Marketing, Human Resources, and Management) of organizations and also will be able to create hypotheses for research proposals. | X | ||||
3 | Will be able to do research for determining changes, diagnosing problems and developing solutions in business world. | X | ||||
4 | Will have a command of qualitative and quantitative research methodology. | X | ||||
5 | Will be able to conduct statistical analyses and interpret the results. | X | ||||
6 | Will have a command of scientific studies (writing articles, presenting papers) | X | ||||
7 | Should have mastery of at least one foreign language at a scientific level to be able to realize cross-cultural studies. | X | ||||
8 | Should be able to update his/her professional knowledge and skills continuously to be able to adapt to changes in scientific area. | X | ||||
9 | Should be able to do team work in researches and studies and contribute to information flow. | X | ||||
10 | Will be able to have a holistic approach to Business Administration and prepare a thesis on a special area of the field. | X | ||||
11 | être en mesure d’avoir une perspective globale de la gestion et de fournir une thèse en se spécialisant dans une des sphères de ce domaine. |
Activities | Number | Period | Total Workload |
---|---|---|---|
Total Workload | 0 | ||
Total Workload / 25 | 0.00 | ||
Credits ECTS | 0 |