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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Logistic Regression Analysis * ISB   414 8 3 3 5

 Prerequisites and co-requisites Yok Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof. Dr. Mahmude Revan ÖZKALE
Instructors
 Prof. Dr. MAHMUDE REVAN ÖZKALE 1. Öğretim Grup:A Prof. Dr. MAHMUDE REVAN ÖZKALE 2. Öğretim Grup:A

Assistants
Goals
To construct the necessary theoretical and applied background in undergraduate teaching, to analyze the binary response data that can be faced at the public and private sectors, to gain the knowledge, skills, and practicality for interpreting the results of the analysis.
Content
Fitting a binary logistik regression model and interpret the results.

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
X
2
Emphasize the importance of Statistics in life
X
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
X
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
X
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
X
13
Distinguish the difference between the statistical methods
X
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Binary logistic regression Source reading and use of statistical package program
2 Logit, odds ratio, relative risk Source reading and use of statistical package program
3 Multiple logistic regression and fiting a model, mariginal effect Source reading and use of statistical package program
4 Maximum likelihood and Newton-Raphson method Source reading and use of statistical package program
5 Confidence intervals Source reading and use of statistical package program
6 Goodness of fit Source reading and use of statistical package program
7 Lack of fit tests Source reading and use of statistical package program
8 Midterm exam Review the topics discussed in the lecture notes and sources
9 Classification tables Source reading and use of statistical package program
10 Regression diagnostic and outliers Source reading and use of statistical package program
11 ROC curve Source reading and use of statistical package program
12 Sensitivity, specificity and related topics Source reading and use of statistical package program
13 Modeling strategies Source reading and use of statistical package program
14 Modeling strategies for assessing interaction and confounding Source reading and use of statistical package program
15 Application of logisitc regression with different sampling models Source reading and use of statistical package program
16-17 Final exam Review the topics discussed in the lecture notes and sources