ISB499 Categorical Data Analysis

2 ECTS - 2-0 Duration (T+A)- 7. Semester- 2 National Credit

Information

Code ISB499
Name Categorical Data Analysis
Semester 7. Semester
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 2 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. SELMA TOKER KUTAY


Course Goal

The aim of this course is to introduce the contingency tables and to examine the analysis methods based on these tables.

Course Content

Describing and classifying the categorical variables, Probability distributions for analyzing categorical data, Describing contingency tables, Advanced methods in contingency tables, Loglinear models for contingency tables

Course Precondition

None

Resources

Sosyal Bilimlerde Kategorik Verilerle İlişki Analizi, Çiğdem ARICIGİL ÇİLAN, Pegem Yayınevi, 2013

Notes

Lecture Notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learn to define and classify categorical variables.
LO02 Learn to define the contingency tables.
LO03 Compute joint, marginal and conditional probabilities of contingency tables.
LO04 Apply advanced methods in contingency tables.
LO05 Examine log-linear models in contingency tables.
LO06 Learn to built models for the categorical data.
LO07 Learn the apply statistical analysis methods to the categorical variables.
LO08 Analyze the results by using SPSS.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 3
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 3
PLO03 Bilgi - Kuramsal, Olgusal Define basic principles and concepts in the field of Law and Economics
PLO04 Bilgi - Kuramsal, Olgusal Produce numeric and statistical solutions in order to overcome the problems 3
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 4
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer systems and softwares 2
PLO07 Bilgi - Kuramsal, Olgusal Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 3
PLO08 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 4
PLO09 Bilgi - Kuramsal, Olgusal Make statistical inference(estimation, hypothesis tests etc.) 3
PLO10 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques 2
PLO11 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programme 2
PLO12 Bilgi - Kuramsal, Olgusal Construct a model and analyze it by using statistical packages 4
PLO13 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods 3
PLO14 Beceriler - Bilişsel, Uygulamalı Be aware of the interaction between the disciplines related to statistics 3
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 3
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 2
PLO17 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği 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
PLO18 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection 3


Week Plan

Week Topic Preparation Methods
1 Defining and classifying categorical variables Review of the literature Öğretim Yöntemleri:
Anlatım, Tartışma
2 Probability distributions for analyzing categorical data Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
3 Describing contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
4 Computing joint, marginal and conditional probabilities of two way contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
5 Chi-squared tests of independence Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
6 Defining three way contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
7 Marginal and conditional odds ratio and independence for three way contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
8 Mid-Term Exam General review Ölçme Yöntemleri:
Yazılı Sınav
9 Tests for three way contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
10 Coefficients of relation in the contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
11 Advanced methods in contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
12 Loglinear Models in Two-Way Tables, Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
13 Log-linear models in three way contingency tables Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
14 Log-linear model fitting Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
15 The relation between the binomial logit and log-linear model Review of the previous lecture and the literature Öğretim Yöntemleri:
Anlatım, Tartışma
16 Term Exams General review Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams General review Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 2 28
Out of Class Study (Preliminary Work, Practice) 14 1 14
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 4 4
Final Exam 1 8 8
Total Workload (Hour) 54
Total Workload / 25 (h) 2,16
ECTS 2 ECTS