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| EKO2000 | Statistics | 3+0+0 | ECTS:5 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of PUBLIC ADMINISTRATION | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Mustafa KÖSEOĞLU | | Co-Lecturer | Frof. Dr. Mustafa Köseoğlu | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to present descriptive statistical knovledge and some statistical ınference methods. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | calculate and interpret some basic descriptive statistics. | 1,2 | | | LO - 2 : | discriminate between real and nominal variables | 1,2 | | | LO - 3 : | learn basic probability rules and apply them to decision making problems | 1,2 | | | LO - 4 : | recognize some probability distributions and use them in order to solve business problems | 1,2 | | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Basic Concepts, Statistical Presentations, Location and Variability Measures, Probability, Random Variables, Expected Value and Variance, Distributions of random Variables, Sampling, Point and Interval Estimation, Hypothesis Tests, Simple Linear Regression, Multiple Regression. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Some basic definitions, levels of measurement: nominal, ordinal, interval and ratio scales.
| | | Week 2 | Descriptive Statisctics: mean, weighted mean, median, mod.
| | | Week 3 | range, variance and standart deviation, coefficient of variation. | | | Week 4 | basic index, composite indices: unweighted composite index, weighted (Laspeyres) composite index. | | | Week 5 | Some basic probability concepts, probability rules: additive rule, multiplication rule.
| | | Week 6 | Independent events, conditional probability, joint probability and marginal probability.
| | | Week 7 | Bayes' theorem. | | | Week 8 | discrete stochastic variables, probability distribution function, continuous stochastic variables, probability density function, expeced value.
| | | Week 9 | Mid-term exam | | | Week 10 | Probability Distributions: Bernoulli distribution, Binom distribution, Hypergeometric distribution.
| | | Week 11 | Poisson distribution.
| | | Week 12 | Normal distribution, properties of normal distribution.
| | | Week 13 | introduction to sampling theory: sampling distribution of sample mean.
| | | Week 14 | introduction to sampling theory: sampling distribution of sample proportion. | | | Week 15 | End-of-term exam | | | Week 16 | End-of-term exam | | | |
| 1 | Newbold, P. (Çev. Şenesen, Ü.) 2000; İşletme ve İktisat İçin İstatistik, Literatür Yayıncılık, İstanbul | | | |
| 1 | Türedi, N. 2008; Uygulamalı Temel İstatistik Yöntemler, Celepler Matbaası, Trabzon | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 11/2023 | 1 | 50 | | End-of-term exam | 16 | 01/2024 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 6 | 14 | 84 | | Arasınav için hazırlık | 7 | 1 | 7 | | Arasınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 150 |
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