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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| STATISTICS (MASTER) (WITH THESIS) | |
| Code | ISB561 |
| Name | Statistical Computing |
| Term | 2018-2019 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ALİ İHSAN GENÇ |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to teach students how to do the statistical analyses based on computing tools.
Course Content
Basics of R programming, random number generating from distributions, weak law of large numbers, approximate integral, Monte Carlo methods, bootstrap and jackknife methods
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Generates a random number from a given distribution. |
| LO02 | Demonstrates Monte Carlo methods in statistical inference. |
| LO03 | Computes integrals approximately. |
| LO04 | Computes confidence intervals approximately. |
| LO05 | Uses of the MCMC methods in point estimation. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Have in-depth theoretical and practical knowledge about Probability and Statistics | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | They have the knowledge to make doctoral plans in the field of statistics. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge about analysis and modeling methods used in statistics. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Has comprehensive knowledge of methods used in statistics. | 4 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Make scientific research on Mathematics, Probability and Statistics. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Indicates statistical problems, develops methods to solve. | 3 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply innovative methods to analyze statistical problems. | 2 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Designs and applies the problems faced in the field of analytical modeling and experimental researches. | 2 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Access to information and do research about the source. | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Develops solution approaches in complex situations and takes responsibility. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Has the confidence to take responsibility. | |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | They demonstrate being aware of the new and developing practices. | |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | He/She constantly renews himself/herself in statistics and related fields. | |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Communicate in Turkish and English verbally and in writing. | |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Transmits the processes and results of their studies clearly in written and oral form in national and international environments. | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | It considers the social, scientific and ethical values in the collection, processing, use, interpretation and announcement stages of data and in all professional activities. | 4 |
| PLO17 | Yetkinlikler - Öğrenme Yetkinliği | Uses the hardware and software required for statistical applications. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | R system, R functions, script files, packages and graphics | Source reading | |
| 2 | Random numbers generation, inverse transform method | Source reading | |
| 3 | Accept-reject method, transformation method | Source reading | |
| 4 | Multiple plots | Source reading | |
| 5 | Contour plots | Source reading | |
| 6 | Monte Carlo integration | Source reading | |
| 7 | Variance reduction | Source reading | |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources | |
| 9 | Monte Carlo methods in statistical inference | Source reading | |
| 10 | Bootstrap and jackknife | Source reading | |
| 11 | Permutation tests | Source reading | |
| 12 | MCMC methods | Source reading | |
| 13 | Probability density estimation | Source reading | |
| 14 | Maximum likelihood method | Source reading | |
| 15 | EM algorithm | 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 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||