Statistical Methods in Social Sciences(RI203)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| RI203 | Statistical Methods in Social Sciences | 3 | 2 | 0 | 0 | 2 | 3 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | |
| Course Type | Compulsory |
| Course Level | Bachelor Degree |
| Course Instructor(s) | Aslı Gül ÖNCEL aoncel@gsu.edu.tr (Email) |
| Assistant | |
| Objective |
Course objective is to give to the student the basic knowledge about, • Descriptive statistics (representation of datas, charts, measures of central tendency and dispersion). • Probability distributions (law of sum and product of probabilities, conditional probability, discrete and continuous probability distributions). • Statistical inference and estimation theory. • Parametric and non-parametric hypothesis tests. |
| Content |
1) Introduction to statistics, organization of datas and data analysis. 2) Organization of datas and data analysis, frequency distribution. 3) Descriptive measures of central tendancy and dispersion of distributions. 4) Probability and law of probability. 5) Elementary laws of probability for discrete variables. 6) Elementary laws of probability for continuous variables. 7) Sampling and statistical inference (Estimation of a mean and proportion) 8) Parametric hypothesis testing. 9) Non-parametric hypothesis testing (Test Chi-square of independance and homogeneity) 10) Non-parametric hypothesis testing (Test Chi-square of conformity) |
| Course Learning Outcomes |
At the end of the course, the studient will : 1. Get the basic knowledge and technics of data analysis. 2. Calculate the probability of different events. 3. Display obviously the logic and signification of statistical measures of central tendency and dispersion. 4. Master the statistical tools in social sciences identifying principal caracteristics, words and key concepts of data analysis and statistical inference 5. Apply statistical tests to the considered problems. |
| Teaching and Learning Methods | |
| References |
Bernard Grais, “Statistique descriptive”,3eme edition, Dunod, Paris Vincent Giard, "Statistiques Appliquées a la Gestion", Edition Economica,Paris. Paul Newbold, William L.Carlson, Betty Thorne, “Statistics for Business and Economics”, 6th edition, Prentice Hall, Upper Saddle River, New Jersey, 2007 Roger C. Pfaffenberger, James H. Patterson, “Statistical Methods for Business and Economics”, Irwin 2003 |
Theory Topics
| Week | Weekly Contents |
|---|---|
| 1 | Introduction to statistics |
| 2 | Organization of datas and data analysis, frequency distribution. |
| 3 | Descriptive measures of central tendancy and dispersion of distributions. |
| 4 | Descriptive measures of central tendancy and dispersion of distributions. |
| 5 | Probability and law of probability. |
| 6 | Elementary laws of probability for discrete variables. |
| 7 | Elementary laws of probability for continuous variables. |
| 8 | Sampling and statistical inference (Estimation of a mean and proportion) |
| 9 | Sampling and statistical inference (Estimation of a mean and proportion) |
| 10 | Mid term Exam. |
| 11 | Parametric hypothesis testing. |
| 12 | Parametric hypothesis testing. |
| 13 | Non-parametric hypothesis testing (Test Chi-square of independance and homogeneity) |
| 14 | Non-parametric hypothesis testing (Test Chi-square of conformity) |
Practice Topics
| Week | Weekly Contents |
|---|
Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 9 | 60 |
| Contribution of final exam to overall grade | 1 | 40 |
| Toplam | 10 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 3 | 15 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 25 |
| Project | 0 | 0 |
| Laboratory | 0 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 5 | 20 |
| 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 | 9 | 60 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | To have a detailed knowledge on the principal concepts, actors and components of the international system | |||||
| 2 | To master the fundamentals such as history, law, economics, sociology and political science required by the multidisciplinary nature of International Relations | |||||
| 3 | Pouvoir analyser la pratique à partir d’une infrastructure théorique assimilée | X | ||||
| 4 | To have acquired the capability of specializing on a particular theme and/or region | |||||
| 5 | In the light of Galatasaray University’s traditional and institutional links with Europe, to have developed the ability to contribute to Turkey’s accession process to the EU in a concrete manner | |||||
| 6 | To interpret and explain Turkish foreign policy through its domestic components as well as from the perspective of the international system | |||||
| 7 | To have reached the necessary level of competence to be able to undertake a career at the Ministry of Foreign Affairs as well as other state institutions and/or the private sector | |||||
| 8 | Possess the required skills to work at various international organizations and NGOs | |||||
| 9 | To be in perfect command of French, teaching language of Galatasaray University, and of English, its mandatory language, at the academic -with a view to write a thesis/project/book in the field of International Relations- as well as the professional level | X | ||||
| 10 | To have the capacity to utilize the methodological instruments acquired throughout the studies at any conceptual and/or academic work | X | ||||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 2 | 28 |
| Working Hours out of Class | 5 | 4 | 20 |
| Assignments | 3 | 3 | 9 |
| Midterm Examinations (including preparation) | 1 | 7 | 7 |
| Final Examinations (including preparation) | 1 | 5 | 5 |
| Quiz | 5 | 2 | 10 |
| Total Workload | 79 | ||
| Total Workload / 25 | 3.16 | ||
| Credits ECTS | 3 | ||