Quantitative Methods(ML517)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| ML517 | Quantitative Methods | 2 | 3 | 0 | 0 | 3 | 6 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | Turkish |
| Course Type | Compulsory |
| Course Level | Masters Degree |
| Course Instructor(s) | Başak DEĞERLİ basak_yalcintr@yahoo.com (Email) |
| Assistant | |
| Objective | This course aims to teach the basic concepts, principles and applications related to research methodology and techniques of digital logistics management. |
| Content |
1) Research project, organization and analysis of data. Measures of central tendency and dispersion. 2) Probability and laws of probability. Elementary probability distributions of discrete and continuous random variables. 3) The sampling and statistical inference methods (Estimating the average and the proportion of a population). 4) Parametric hypothesis tests (tests of the mean and the proportion of a population). 5) Parametric hypothesis tests - Comparison of means of two or more populations. Analysis of variance. 6) Parametric hypothesis tests - Comparison of proportions of two populations. Parametric hypothesis tests (Comparison of proportions of multiple populations, Chi2 tests for homogeneity and conformity). 7) Regression analysis - Simple linear regression analysis, multiple regression analysis on Excel and SPSS. 8) Logistics strategy and planning. Forecasting logistics requirements. 9) Inventory policiy decisions. Methods and models of inventory management. 10) Purchaising decisions and order quantity. 11) Linear programming and resolution of models with Simplexe algorithm. Resolution of integer and binary LP problems in Excel. 12) Transportation problem and decisions. |
| Course Learning Outcomes |
At the end of the course, the studient will be able to : 1. Implement a research project in logistics. 2. Develop new ideas and models have acquired strategic importance of logistics 3. Analyze the process of logistics management using quantitatives methods, interpret the data and find a solution to the problems considered. 4. Adapt the methods and models of inventory management to the problems encountered in his professional life. 5. Monitor developments concerning logistics management and develop his professional knowledge. |
| Teaching and Learning Methods | |
| References |
Daniel Wayne W. & Terrell James C., Business Statistics, 5. edition, Houghton Miflin, USA, 1989. Kobu, Bülent. Üretim Yönetimi, Genişletilmiş ve güncelleştirilmiş 11. baskı. İstanbul, Avcıol Basım Yayın, 2003. Newbold, Paul, Statistics for Business and Economics, 7. edition, Pearsons Education, NJ 2010. 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 Ronald, H Ballou, Business Logistics Management, Prentice-Hall Inc., 3rd Edition, NY 1992. Ronald, H Ballou, Business Logistics/Supply Chain Management, Pearson Prentice Hall Inc., 5th Edition, NJ 2004. Stock, James R. ve Douglas M. Lambert. Strategic Logistics Management, 4. b. Singapore, Mc Graw-Hill, 2001. Zipkin, Paul H., Foundations of Inventory Management, USA: Mc Graw-Hill, 2000. |
Theory Topics
| Week | Weekly Contents |
|---|---|
| 1 | Introduction to logistics management, research project, organization and analysis of data. Measures of central tendency and dispersion. |
| 2 | Probability and laws of probability. Elementary probability distributions of discrete and continuous random variables. |
| 3 | The sampling and statistical inference methods (Estimating the average and the proportion of a population). |
| 4 | Parametric hypothesis tests (tests of the mean and the proportion of a population). |
| 5 | Parametric hypothesis tests - Comparison of means of two or more populations. Analysis of variance. |
| 6 | Parametric hypothesis tests - Comparison of proportions of two populations. Parametric hypothesis tests (Comparison of proportions of multiple populations, Chi2 tests for homogeneity and conformity). |
| 7 | Regression analysis - Simple linear regression analysis, multiple regression analysis on Excel and SPSS. |
| 8 | Mid term. |
| 9 | Logistics strategy and planning. Forecasting logistics requirements. |
| 10 | Inventory policiy decisions. Methods and models of inventory management. |
| 11 | Purchasing decisions and order quantity. |
| 12 | Linear programming and resolution of models with Simplexe algorithm. Resolution of integer and binary LP problems in Excel. |
| 13 | Transportation problem and decisions. |
| 14 | Transportation problem and decisions. |
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 | 1 | 25 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 25 |
| 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 | ||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 3 | 42 |
| Working Hours out of Class | 11 | 4 | 44 |
| Assignments | 1 | 15 | 15 |
| Midterm Examinations (including preparation) | 1 | 20 | 20 |
| Final Examinations (including preparation) | 1 | 32 | 32 |
| Total Workload | 153 | ||
| Total Workload / 25 | 6.12 | ||
| Credits ECTS | 6 | ||