ISB352 Statistical Inference

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

Information

Code ISB352
Name Statistical Inference
Term 2024-2025 Academic Year
Semester 6. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 5 ECTS
National Credit 3 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 Instructor
1 2
Doç. Dr. SELMA TOKER KUTAY (A Group) (Ins. in Charge)


Course Goal / Objective

The aim of the course is to teach how to do hypothesis testing for parameters and estimate the parameters.

Course Content

statistics and distributions, sampling and statistics,Sampling distribution function and some related statistics, sampling density function, sampling percentage, Hypothesis testing, simple and compound hypothesis, test function, Neymann-Pearson lemma , application of Neymann-Pearson lemma, Bayes tests, power functions, UMPT, p-value are the contents of this course.

Course Precondition

None

Resources

İstatistiksel Tahmin Teorisi, Özge AKKUŞ , Süleyman GÜNAY, Gazi Kitabevi, 2016.

Notes

Lecture Notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Have knowledge about finding test statistics.
LO02 Learn the statistics and distributions.
LO03 Have knowledge about choosing estimator for the population parameters.
LO04 Learn the statistical inference for parameters
LO05 Have knowledge about simple and compound hypothesis
LO06 Learn to apply hypothesis testis.
LO07 Learn the likelihood principle and likelihood ratio test.
LO08 Learn bayes confidence intervals and approximate confidence intervals.


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 Statistics
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
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 2
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization
PLO07 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 2
PLO08 Bilgi - Kuramsal, Olgusal Make statistical inference (estimation, hypothesis tests etc.)
PLO09 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques and gain insight
PLO10 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programs
PLO11 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 2
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 2
PLO14 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
PLO15 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection


Week Plan

Week Topic Preparation Methods
1 Statistics and distributions, sampling and statistics Review of the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
2 Sampling distribution function and some related statistics, sampling density function, sampling percentage Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
3 Skor function and fisher information. Data reductions Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
4 Completeness, likelihood principle Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
5 Parameter estimation methods (ML, moments, OLS, Bayes) Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
6 Hypothesis testing, simple and compound hypothesis, test function Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
7 Likelihood ratio test Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
8 Mid-Term Exam General review Ölçme Yöntemleri:
Yazılı Sınav
9 Neymann-Pearson lemmaı , application of Neymann-Pearson lemma Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
10 Bayes tests, power functions, UMPT, p-value Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
11 Application of Hypothesis testing Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
12 Application of Hypothesis testing-2 Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
13 Confidence intervals, point estimation Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
14 Bayes confidence intervals, approximate confidence intervals Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
15 Confidence intervals using Pivot Review of the previous lesson and the literature Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
16 Final Term Exam General review Ölçme Yöntemleri:
Yazılı Sınav, Ödev
17 Final Term Exam General review Ölçme Yöntemleri:
Yazılı Sınav, Ödev


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 18 18
Total Workload (Hour) 114
Total Workload / 25 (h) 4,56
ECTS 5 ECTS

Update Time: 09.05.2024 02:22