ISB508 Categorical Data Analysis

6 ECTS - 3-0 Duration (T+A)- 2. Semester- 3 National Credit

Information

Unit INSTITUTE OF NATURAL AND APPLIED SCIENCES
STATISTICS (MASTER) (WITH THESIS)
Code ISB508
Name Categorical Data Analysis
Term 2018-2019 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Belirsiz
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. DENİZ ÜNAL ÖZPALAMUTCU
Course Instructor
The current term course schedule has not been prepared yet.


Course Goal / Objective

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Course Content

Defining two-way probability tables, Statistical results for two-way probability tables, Models for binary response variables, Logline models, Logit models, Multinomial response models, Models for paired couples, Repeated categorical response data analysis, Asymptotic theory for parametric models, Estimation theory for parametric models.

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Have in-depth theoretical and practical knowledge about Probability and Statistics
LO02 Make scientific research on Mathematics, Probability and Statistics.
LO03 They have the knowledge to make doctoral plans in the field of statistics.
LO04 Has comprehensive knowledge about analysis and modeling methods used in statistics.
LO05 Comprehensive knowledge of methods used in statistics.
LO06 Indicates statistical problems, develops methods to solve.
LO07 Apply innovative methods to analyze statistical problems.
LO08 Designs and applies the problems faced in the field of analytical modeling and experimental researches.
LO09 Access to information and do research about the source.
LO10 Develops solution approaches in complex situations and takes responsibility.
LO11 It has the confidence to take responsibility.
LO12 He demonstrates that he is aware of his / her new and developing practices.
LO13 Transmits the processes and results of their studies clearly in written and oral form in national and international environments.
LO14 It considers the social, scientific and ethical values in the collection, processing, use, interpretation and announcement stages of data and in all professional activities.
LO15 It constantly renews itself in statistics and related fields.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Have in-depth theoretical and practical knowledge about Probability and Statistics
PLO02 - They have the knowledge to make doctoral plans in the field of statistics.
PLO03 - Has comprehensive knowledge about analysis and modeling methods used in statistics.
PLO04 - Has comprehensive knowledge of methods used in statistics.
PLO05 - Make scientific research on Mathematics, Probability and Statistics.
PLO06 - Indicates statistical problems, develops methods to solve.
PLO07 - Apply innovative methods to analyze statistical problems.
PLO08 - Designs and applies the problems faced in the field of analytical modeling and experimental researches.
PLO09 - Access to information and do research about the source.
PLO10 - Develops solution approaches in complex situations and takes responsibility.
PLO11 - Has the confidence to take responsibility.
PLO12 - They demonstrate being aware of the new and developing practices.
PLO13 - He/She constantly renews himself/herself in statistics and related fields.
PLO14 - Communicate in Turkish and English verbally and in writing.
PLO15 - Transmits the processes and results of their studies clearly in written and oral form in national and international environments.
PLO16 - It considers the social, scientific and ethical values ​​in the collection, processing, use, interpretation and announcement stages of data and in all professional activities.
PLO17 - Uses the hardware and software required for statistical applications.


Week Plan

Week Topic Preparation Methods
1 Definitions none
2 contingency tables study of proposed resources
3 Two dimensional contingency tables study of proposed resources
4 Two dimensional contingency tables study of proposed resources
5 three-dimensional contingency tables study of proposed resources
6 Contingency tables and their analysis with three or more entries study of proposed resources
7 Contingency tables and their analysis with three or more entries study of proposed resources
8 Mid-Term Exam exam
9 Relationship measures study of proposed resources
10 Multi-dimensional tables study of proposed resources
11 Logarithmic linear models study of proposed resources
12 Logit model study of proposed resources
13 Multinomial logit model study of proposed resources
14 Probit regression analysis with Logit and Multinomial logit model study of proposed resources
15 Quadratic table analysis study of proposed resources
16 Term Exams exam
17 Term Exams exam

Update Time: 21.11.2018 05:55