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Information
| Code | ISB351 |
| Name | Computational Statistics |
| Term | 2022-2023 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 |
| Label | C Compulsory |
| 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
Starting with the basics of a program, the exploratory data analysis and statistical inference methods are studied.
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 | Comprehends the basics of a statistical package, for instance R. |
| LO02 | Plots univariate data. |
| LO03 | Plots bivariate data. |
| LO04 | Comprehends the properties of specific distributions. |
| 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 Probability, Statistics and Mathematics | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | 5 |
| 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 | 4 |
| 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 | 5 |
| 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 | 4 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 4 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Make statistical inference(estimation, hypothesis tests etc.) | 5 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques | 3 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programme | |
| PLO12 | Bilgi - Kuramsal, Olgusal | Construct a model and analyze it by using statistical packages | 5 |
| 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 | |
| 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 | |
| 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 | Data types, program basics | Source reading | |
| 2 | Program basics | Source reading | |
| 3 | Univariate data, categorical data, contingency tables | Source reading | |
| 4 | Graphs for categorical data, barplots, pie charts | Source reading | |
| 5 | Summarization of a numerical data, mean, variance, mode, median | Source reading | |
| 6 | Numerical data plots, histogram, stem-leaf plots | Source reading | |
| 7 | Boxplots, standardization of data | Source reading | |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources | |
| 9 | Simulation | Source reading | |
| 10 | Normal distribution and some other distributions | Source reading | |
| 11 | Regression and probability plots | Source reading | |
| 12 | Confidence intervals | Source reading | |
| 13 | Confidence intervals II | Source reading | |
| 14 | Hypothesis tests | Source reading | |
| 15 | Hypothesis tests II | Source reading | |
| 16 | Term Exams | Review the topics discussed in the lecture notes and sources | |
| 17 | Term Exams | Review the topics discussed in the lecture notes and sources |
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 | ||