Course Detail
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| STATISTICS II | ULY2234160 | Spring Semester | 3+0 | 3 | 5 |
| Course Program | Cuma 11:00-11:45 Cuma 12:00-12:45 Cuma 12:45-13:30 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | Turkish |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Required |
| Course Coordinator | Assist.Prof. Mutlu GÜRSOY |
| Name of Lecturer(s) | Assist.Prof. Recep ÖZSÜRÜNÇ |
| Assistant(s) | |
| Aim | Students are aimed to understand the logic of inferential statistics and to apply hypothesis testing and regression analysis for simple business problems |
| Course Content | This course contains; Introduction to Hypothesis Testing , Five - Step Procedure for Hypothesis Testing ,z and t Tests About a Population Mean, z Tests About a Population Proportion ,Sample Size Determination, The Chi – Square Distribution and Statistical Inference for Population Variance , One – Sample Hypothesis Testing Using EXCEL and SPSS,Statistical Inference Based On Two Samples ,Comparing Two Population Proportions and Variances by Using Large Independent Samples ,Two Sample HypothesisTesting Using Excel and SPSS ,Experimental Design and Analysis of Variance ,Two – Way Analysis of Variance ,Chi – Square Tests ,Simple Linear Regression Analysis,Regression Analysis - Confidence and Prediction Intervals ,Simple Coefficients of Determination and Correlation, An F – Test for the Model, Residual Analysis . |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1. Will be able to explain the logic of hypothesis testing | 16, 6, 9 | A |
| 1.1 Locate hypothesis testing in inferential statistics | A | |
| 1.2 Set up appropriate null and alternative hypotheses | A | |
| 1.3 Describe Type I and Type II errors and their probabilities | A | |
| 2. Will be able to translate one – sample hypothesis tests | 16, 6, 9 | A |
| 2.1 Use critical values and p-values to perform a z test about a population mean | A | |
| 2.2 Use critical values and p-values to perform a t-test about a population mean | A | |
| 2.3 Use critical values and p-values to perform a large sample z test about a population proportion. | A | |
| 3. Will be able to use technology for one – sample hypothesis testing | 16, 6, 9 | A |
| 3.1 Realize one – sample tests using Excel | A | |
| 3.2 Realize one – sample tests using SPSS | A | |
| 4. Will be able to locate two – sample hypothesis tests | 16, 6, 9 | A |
| 4.1 Compare two population means when the samples are independent | A | |
| 4.2 Recognize when data come from independent samples and when they are paired | A | |
| 4.3 Compare two population means when the data are paired | A | |
| 5. Will be able to use technology for two – sample hypothesis testing | 16, 6, 9 | A |
| 5.1 Realize two – sample tests using Excel | A | |
| 5.2 Realize two – sample tests using SPSS | A | |
| 6. Will be able to tell Analysis of Variance | 16, 6, 9 | A |
| 6.1 Explain the basic terminology and concepts of experimental design | A | |
| 6.2 Compare several different population means by using a one-way analysis of variance | A | |
| 6.3 Compare treatment effects and block effects by using a randomized block design | A | |
| 7. Will be able to use simple regression analysis | 16, 6, 9 | A |
| 7.1 Explain the simple linear regression model | A | |
| 7.2 Describe the assumptions behind simple linear regression and the standard error | A | |
| 7.3 Interpret the basic coefficient of determination and the regression coefficient | A |
| Teaching Methods: | 16: Question - Answer Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Hypothesis Testing | |
| 2 | Five - Step Procedure for Hypothesis Testing | |
| 3 | z and t Tests About a Population Mean, z Tests About a Population Proportion | |
| 4 | Sample Size Determination, The Chi – Square Distribution and Statistical Inference for Population Variance | |
| 5 | One – Sample Hypothesis Testing Using EXCEL and SPSS | |
| 6 | Statistical Inference Based On Two Samples | |
| 7 | Comparing Two Population Proportions and Variances by Using Large Independent Samples | |
| 8 | Two Sample HypothesisTesting Using Excel and SPSS | |
| 9 | Experimental Design and Analysis of Variance | |
| 10 | Two – Way Analysis of Variance | |
| 11 | Chi – Square Tests | |
| 12 | Simple Linear Regression Analysis | |
| 13 | Regression Analysis - Confidence and Prediction Intervals | |
| 14 | Simple Coefficients of Determination and Correlation, An F – Test for the Model, Residual Analysis |
| Resources |
| [1] will be available at http://mebis.medipol.edu.tr |
| [2] Bruce L. Bowerman, Richard T. O'Connell, Emily S. Murphree, James B. Orris (2013), İşletme İstatistiğinin Temelleri, 4.basımdan Çeviri, Çeviri Editörleri: N.Orhunbilge, M.Can, Ş.Er, Nobel Akademik Yayıncılık [3] David R. Anderson, Dennis J. Sweeney, Thomas A. Williams (2011), Statistics for Business and Economics, Eleventh Edition, South-Western Cengage Learning |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında teorik bilgileri tanımlar. | ||||||
| 2 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli matematiksel ve istatistiki yöntemleri anlatır. | X | |||||
| 3 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli en az bir bilgisayar programını kullanır. | X | |||||
| 4 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli olan mesleki yabancı dil yeterliliğini gösterir. | ||||||
| 5 | Alanına dair projeler hazırlar ve takım çalışmalarını yönetir. | ||||||
| 6 | Mesleki alanda yaşam boyu öğrenmenin bilinciyle uluslararası lojistik ve tedarik zinciri yönetimi alanında gelişmeleri izleyerek kendini sürekli yenileyip edindiği bilgi ve becerileri eleştirel olarak değerlendirir. | X | |||||
| 7 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında teorik ve uygulamaya yönelik bilgileri kullanır. | ||||||
| 8 | En az A1 düzeyinde bir yabancı dili kullanarak güncel teknolojileri takip eder, sözlü/yazılı iletişim kurar. | ||||||
| 9 | Örgüt/kurumsal, iş ve toplumsal etik değerlerini benimser ve kullanır. | ||||||
| 10 | Topluma hizmet duyarlılığı çerçevesinde, sosyal sorumluluk ilkelerini benimser ve gerektiğinde inisiyatif alır. | ||||||
| 11 | Disiplinler arası çalışmalar yürütebilmek için farklı disiplinlerde temel bilgileri ve verileri analiz ederek alanında kullanır. | X | |||||
| 12 | Uluslararası lojistik ve tedarik zinciri yönetimi sektörlerindeki sorunlar karşısında hem mikro hem makro çerçevede uygun öneriler sunar. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 40 | |
| Rate of Final Exam to Success | 60 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 14 | 2 | 28 | |||
| Guided Problem Solving | 14 | 2 | 28 | |||
| Resolution of Homework Problems and Submission as a Report | 5 | 1 | 5 | |||
| Term Project | 1 | 20 | 20 | |||
| Presentation of Project / Seminar | 1 | 2 | 2 | |||
| Quiz | 2 | 10 | 20 | |||
| Midterm Exam | 1 | 16 | 16 | |||
| General Exam | 1 | 31 | 31 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 150 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(150/30) | 5 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| STATISTICS II | ULY2234160 | Spring Semester | 3+0 | 3 | 5 |
| Course Program | Cuma 11:00-11:45 Cuma 12:00-12:45 Cuma 12:45-13:30 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | Turkish |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Required |
| Course Coordinator | Assist.Prof. Mutlu GÜRSOY |
| Name of Lecturer(s) | Assist.Prof. Recep ÖZSÜRÜNÇ |
| Assistant(s) | |
| Aim | Students are aimed to understand the logic of inferential statistics and to apply hypothesis testing and regression analysis for simple business problems |
| Course Content | This course contains; Introduction to Hypothesis Testing , Five - Step Procedure for Hypothesis Testing ,z and t Tests About a Population Mean, z Tests About a Population Proportion ,Sample Size Determination, The Chi – Square Distribution and Statistical Inference for Population Variance , One – Sample Hypothesis Testing Using EXCEL and SPSS,Statistical Inference Based On Two Samples ,Comparing Two Population Proportions and Variances by Using Large Independent Samples ,Two Sample HypothesisTesting Using Excel and SPSS ,Experimental Design and Analysis of Variance ,Two – Way Analysis of Variance ,Chi – Square Tests ,Simple Linear Regression Analysis,Regression Analysis - Confidence and Prediction Intervals ,Simple Coefficients of Determination and Correlation, An F – Test for the Model, Residual Analysis . |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 1. Will be able to explain the logic of hypothesis testing | 16, 6, 9 | A |
| 1.1 Locate hypothesis testing in inferential statistics | A | |
| 1.2 Set up appropriate null and alternative hypotheses | A | |
| 1.3 Describe Type I and Type II errors and their probabilities | A | |
| 2. Will be able to translate one – sample hypothesis tests | 16, 6, 9 | A |
| 2.1 Use critical values and p-values to perform a z test about a population mean | A | |
| 2.2 Use critical values and p-values to perform a t-test about a population mean | A | |
| 2.3 Use critical values and p-values to perform a large sample z test about a population proportion. | A | |
| 3. Will be able to use technology for one – sample hypothesis testing | 16, 6, 9 | A |
| 3.1 Realize one – sample tests using Excel | A | |
| 3.2 Realize one – sample tests using SPSS | A | |
| 4. Will be able to locate two – sample hypothesis tests | 16, 6, 9 | A |
| 4.1 Compare two population means when the samples are independent | A | |
| 4.2 Recognize when data come from independent samples and when they are paired | A | |
| 4.3 Compare two population means when the data are paired | A | |
| 5. Will be able to use technology for two – sample hypothesis testing | 16, 6, 9 | A |
| 5.1 Realize two – sample tests using Excel | A | |
| 5.2 Realize two – sample tests using SPSS | A | |
| 6. Will be able to tell Analysis of Variance | 16, 6, 9 | A |
| 6.1 Explain the basic terminology and concepts of experimental design | A | |
| 6.2 Compare several different population means by using a one-way analysis of variance | A | |
| 6.3 Compare treatment effects and block effects by using a randomized block design | A | |
| 7. Will be able to use simple regression analysis | 16, 6, 9 | A |
| 7.1 Explain the simple linear regression model | A | |
| 7.2 Describe the assumptions behind simple linear regression and the standard error | A | |
| 7.3 Interpret the basic coefficient of determination and the regression coefficient | A |
| Teaching Methods: | 16: Question - Answer Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Hypothesis Testing | |
| 2 | Five - Step Procedure for Hypothesis Testing | |
| 3 | z and t Tests About a Population Mean, z Tests About a Population Proportion | |
| 4 | Sample Size Determination, The Chi – Square Distribution and Statistical Inference for Population Variance | |
| 5 | One – Sample Hypothesis Testing Using EXCEL and SPSS | |
| 6 | Statistical Inference Based On Two Samples | |
| 7 | Comparing Two Population Proportions and Variances by Using Large Independent Samples | |
| 8 | Two Sample HypothesisTesting Using Excel and SPSS | |
| 9 | Experimental Design and Analysis of Variance | |
| 10 | Two – Way Analysis of Variance | |
| 11 | Chi – Square Tests | |
| 12 | Simple Linear Regression Analysis | |
| 13 | Regression Analysis - Confidence and Prediction Intervals | |
| 14 | Simple Coefficients of Determination and Correlation, An F – Test for the Model, Residual Analysis |
| Resources |
| [1] will be available at http://mebis.medipol.edu.tr |
| [2] Bruce L. Bowerman, Richard T. O'Connell, Emily S. Murphree, James B. Orris (2013), İşletme İstatistiğinin Temelleri, 4.basımdan Çeviri, Çeviri Editörleri: N.Orhunbilge, M.Can, Ş.Er, Nobel Akademik Yayıncılık [3] David R. Anderson, Dennis J. Sweeney, Thomas A. Williams (2011), Statistics for Business and Economics, Eleventh Edition, South-Western Cengage Learning |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında teorik bilgileri tanımlar. | ||||||
| 2 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli matematiksel ve istatistiki yöntemleri anlatır. | X | |||||
| 3 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli en az bir bilgisayar programını kullanır. | X | |||||
| 4 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında gerekli olan mesleki yabancı dil yeterliliğini gösterir. | ||||||
| 5 | Alanına dair projeler hazırlar ve takım çalışmalarını yönetir. | ||||||
| 6 | Mesleki alanda yaşam boyu öğrenmenin bilinciyle uluslararası lojistik ve tedarik zinciri yönetimi alanında gelişmeleri izleyerek kendini sürekli yenileyip edindiği bilgi ve becerileri eleştirel olarak değerlendirir. | X | |||||
| 7 | Uluslararası lojistik ve tedarik zinciri yönetimi alanında teorik ve uygulamaya yönelik bilgileri kullanır. | ||||||
| 8 | En az A1 düzeyinde bir yabancı dili kullanarak güncel teknolojileri takip eder, sözlü/yazılı iletişim kurar. | ||||||
| 9 | Örgüt/kurumsal, iş ve toplumsal etik değerlerini benimser ve kullanır. | ||||||
| 10 | Topluma hizmet duyarlılığı çerçevesinde, sosyal sorumluluk ilkelerini benimser ve gerektiğinde inisiyatif alır. | ||||||
| 11 | Disiplinler arası çalışmalar yürütebilmek için farklı disiplinlerde temel bilgileri ve verileri analiz ederek alanında kullanır. | X | |||||
| 12 | Uluslararası lojistik ve tedarik zinciri yönetimi sektörlerindeki sorunlar karşısında hem mikro hem makro çerçevede uygun öneriler sunar. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 40 | |
| Rate of Final Exam to Success | 60 | |
| Total | 100 | |