ISB351 Computational Statistics

5 ECTS - 2-2 Duration (T+A)- 5. Semester- 3 National Credit

Information

Code ISB351
Name Computational Statistics
Term 2024-2025 Academic Year
Semester 5. Semester
Duration (T+A) 2-2 (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 Prof. Dr. ALİ İHSAN GENÇ
Course Instructor Prof. Dr. ALİ İHSAN GENÇ (A Group) (Ins. in Charge)


Course Goal / Objective

This course aims that students do the statistical analyses with a computer program.

Course Content

The scope is the exploratory data analysis and statistical inference methods by starting with the basics of R program.

Course Precondition

None

Resources

Using R for Introductory Statistics, John Verzani, Chapman and Hall/ CRC, Boca Raton, 2005.

Notes

Statistical Computing with R, Maria L. Rizzo, First Edition (Chapman and Hall/CRC The R Series), 2007.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explains the basics of a statistical package, for instance R.
LO02 Plots univariate data.
LO03 Plots bivariate data.
LO04 Finds the properties of specific distributions via computer.
LO05 Perfoms computer simulations.
LO06 Computes probabilities using a computer.
LO07 Finds confidence intervals.
LO08 Does the hypotheses tests.


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 4
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 4
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 4
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 3
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually
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 Data types, program basics Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
2 Program basics Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
3 Univariate data, categorical data, contingency tables Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
4 Graphs for categorical data, barplots, pie charts Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
5 Summarization of a numerical data, mean, variance, mode, median Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
6 Numerical data plots, histogram, stem-leaf plots Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
7 Boxplots, standardization of data Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
8 Mid-Term Exam Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav
9 Simulation Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
10 Normal distribution and some other distributions Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
11 Regression and probability plots Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
12 Confidence intervals Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
13 Confidence intervals II Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
14 Hypothesis tests Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
15 Hypothesis tests II Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
16 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 4 56
Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
Homeworks, Projects, Others 1 3 3
Mid-term Exams (Written, Oral, etc.) 1 8 8
Final Exam 1 16 16
Total Workload (Hour) 125
Total Workload / 25 (h) 5,00
ECTS 5 ECTS

Update Time: 11.06.2024 01:56