| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Statıstıcs For Informatıon Technologıes | ISE 509 | 0 | 3 + 0 | 3 | 6 |
| Ön Koşul Dersleri | |
| Önerilen Seçmeli Dersler | |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | YUKSEK_LISANS |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Dr.Öğr.Üyesi BURCU ÇARKLI YAVUZ |
| Dersi Verenler | |
| Dersin Yardımcıları | |
| Dersin Kategorisi | Diğer |
| Dersin Amacı | Modeling complex multivariable problems, using statistical techniques that can be used in the analysis of multivariate data, interpreting the results of multivariate analyzes and testing their validity. |
| Dersin İçeriği | This course includes advanced statistical techniques used in the analysis and interpretation of data in the areas of information systems: Basic Concepts, Linear Regression Analysis, Multiple Linear Regression Analysis, Dummy Variable Regression Analysis, Nonlinear Regression Analysis, Regulatory and Intermediary Variables, Repeated Sampling, Maximum Likelihood and EM Algorithm, Time Series Analysis, Variance Analysis and Experimental Design, Multivariate Analysis of Variance, Principal Component Analysis, Hierarchical Clustering Methods, Non-hierarchical Clustering Methods and Self-Regulating Maps. |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | To be able to design quantitative research including hypothesis, determining appropriate sample and validation | Lecture, Drilland Practice, Demonstration, | Testing, Homework, |
| 2 | To be able to explain the statistical theory and operational procedures necessary for univariate and multivariate analyzes | Lecture, Question-Answer, Drilland Practice, | Testing, Homework, |
| 3 | To be able to model the change in the dependent variable (s) corresponding to the change in the independent variable (s) and evaluate the assumptions underlying the analysis | Lecture, Question-Answer, Drilland Practice, | Testing, Homework, |
| 4 | To be able to model complex multivariate problems | Lecture, Question-Answer, Drilland Practice, Demonstration, | Testing, Homework, |
| 5 | Ability to analyze samples with small volumes and / or missing data | Lecture, Question-Answer, Drilland Practice, | Testing, Homework, |
| 6 | To be able to design experiments related to group averages and test them with significance tests | Lecture, Question-Answer, Drilland Practice, | Testing, Homework, |
| 7 | Reduce complex high-dimensional data sets to independent low-dimensional spaces | Lecture, Question-Answer, Drilland Practice, Demonstration, | Testing, Homework, |
| 8 | Have the knowledge and ability to divide multivariate data into common subgroups. | Lecture, Question-Answer, Demonstration, | Testing, Homework, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Sampling and Principles, Measurement, Techniques Introduction | |
| 2 | Linear Regression Analysis | |
| 3 | Multiple Linear Regression Analysis | |
| 4 | Dummy Variable and Nonlinear Regression | |
| 5 | Regulatory and Intermediary Variables, Repetitive Sampling | |
| 6 | Maximum Likelihood and EM Algorithm | |
| 7 | Time Series Analysis | |
| 8 | Analysis of Variance and Experimental Design | |
| 9 | Multivariate Analysis of Variance | |
| 10 | Size Reduction | |
| 11 | Example applications | |
| 12 | Clustering Analysis I | |
| 13 | Clustering Analysis II | |
| 14 | Clustering Analysis III |
| Kaynaklar | |
|---|---|
| Ders Notu | www.sabis.sakarya.edu.tr course notes will be shared. |
| Ders Kaynakları | 1. Johnson R.A. and Wichern D.W., (2007), Applied Multivariate Statistical Analysis, 6th edition, Pearson, New Jersey. 2. Hair J.F., Anderson R.E., Tatham R.L. and Black W.C., (2009), Multivariate Data Analysis, 7th edition, Prentice Hall, New Jersey. 3. Ramachandran K.M. and Tsokos C.P., (2009), Mathematical Statistics with Applications, Elsevier Academic Press, Burlington. |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | |||||||
| 2 | |||||||
| 3 | |||||||
| 4 | |||||||
| 5 | |||||||
| 6 | |||||||
| 7 | |||||||
| 8 | |||||||
| 9 | |||||||
| 10 | |||||||
| 11 | |||||||
| 12 | |||||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 50 |
| 1. Kısa Sınav | 20 |
| 1. Ödev | 30 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 50 |
| 1. Final | 50 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 3 | 48 |
| Mid-terms | 1 | 10 | 10 |
| Quiz | 1 | 10 | 10 |
| Assignment | 1 | 10 | 10 |
| Oral Examination | 1 | 5 | 5 |
| Performance Task (Application) | 1 | 5 | 5 |
| Final examination | 1 | 5 | 5 |
| Toplam İş Yükü | 141 | ||
| Toplam İş Yükü / 25 (Saat) | 5,64 | ||
| Dersin AKTS Kredisi | 6 | ||