Application of Statistics for the Social Sciences(COM336)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| COM336 | Application of Statistics for the Social Sciences | 6 | 2 | 0 | 0 | 2 | 3 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | Turkish |
| Course Type | Compulsory |
| Course Level | Bachelor Degree |
| Course Instructor(s) | Orhan İlker BAŞARAN oibasaran@gsu.edu.tr (Email) |
| Assistant | |
| Objective |
Course objective is to give to the student the basic knowledge concerning the following subjects and to provide him using them when faced : • Descriptive statistics (representation of datas, charts, measures of central tendency and dispersion). • Probability and probability laws (law of sum and product of probabilities, conditional probability), theoretical probability distributions for discret and continuous random variables (binomial, Poisson, hypergeometric, Gaussian and Student (t) probability distributions). • Concept of sampling and sampling methods. • Statistical inference and estimation theory (estimation of a mean, a proportion, estimation by confidence interval). • Parametric hypothesis tests (test of a mean, a proportion, comparaison of means or proportions of two populations). |
| Content |
1) Introduction to statistics, steps of a research project, organization of datas and data analysis. 2) Organization of datas and data analysis, frequency distribution. 3)Graphic representation of frequency distributions. 4) Descriptive measures of central tendancy and dispersion of distributions. 5) Concept and laws of probability. 6) Elementary laws of discrete variables. 7) Elementary laws of continuous variables. 8) Mid-term Exam. 9) Sampling and statistical inference (Estimation of a mean and proportion). 10) Parametric hypothesis testing. (Test of a mean or a proportion) 11) Non-parametric hypothesis testing. (Test Chi-2 of independence and homogeneity) |
| Course Learning Outcomes |
At the end of the course, the studient will : 1) Get the basic knowledge and technics of data analysis and graphical representation of datas. 2) Calculate the probability of different events using appropriate probability laws and distributions. 3) Display obviously the logic and signification of statistical measures and methods. 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. 6) Take the approppriate decision by using statistical methods. |
| Teaching and Learning Methods | |
| References |
Calot, Gérard, Cours de Statistique Descriptive, Dunod, Paris Çakır, Filiz, Sosyal Bilimlerde İstatistik, Alfa Yayınları, 2000 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, Tanımsal İstatistik, Olasılık ve Olasılık Dağılımları, İ.Ü.İşletme Fak. Yayınları Avcıol Basım Yayın, İstanbul 2000 Orhunbilge, Prof. Dr. Neyran, Örnekleme Yöntemleri ve Hipotez Testleri, İ.Ü.İşletme Fak. Yayınları Avcıol Basım Yayın, 2. Baskı, İstanbul 2000 |
Theory Topics
| Week | Weekly Contents |
|---|
Practice Topics
| Week | Weekly Contents |
|---|
Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 1 | 40 |
| Contribution of final exam to overall grade | 1 | 60 |
| Toplam | 2 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 40 |
| 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 | 1 | 40 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 2 | 28 |
| Working Hours out of Class | 13 | 2 | 26 |
| Midterm Examinations (including preparation) | 1 | 15 | 15 |
| Total Workload | 69 | ||
| Total Workload / 25 | 2,76 | ||
| Credits ECTS | 3 | ||