BİS630 Time Series Analysis

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

Information

Code BİS630
Name Time Series Analysis
Term 2022-2023 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 7 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator
Course Instructor
1


Course Goal / Objective

The main purpose of this course is to provide the ability to create models with time series and to analyze these models.

Course Content

In this course, subjects such as time series graphing, transformations, stationarity, trend, autocorrelation, model determination and seasonal models will be covered at graduate level.

Course Precondition

none

Resources

The Analysis of Time-series: An Introduction with R by Chris Chatfield and Haipeng Xing Bozkurt, H. (2003). Zaman Serileri Analizi, Bursa: Ekin Kitabevi. Time Series Analysis and Its Applications With R Examples. Authors: Robert H. Shumway, David S. Stoffer

Notes

Time Series Analysis: Forecasting and Control (Wiley Series in Probability and Statistics) 5th Edition


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Students develop their knowledge of biostatistics through time series.
LO02 Concepts such as “stationarity, trend, seasonal effect”, which are frequently encountered in time series, are reinforced.
LO03 Tests some theories about time series.
LO04 Applies and interprets tests related to time series.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Comprehends the original definitions, concepts and theorems that will bring innovation to the field based on the qualifications gained in the biostatistics master's program. 4
PLO02 Bilgi - Kuramsal, Olgusal Using knowledge that requires expertise, analyzes, evaluates and interprets new and complex ideas in the field and related fields.
PLO03 Bilgi - Kuramsal, Olgusal He/She has advanced knowledge about technological tools and software that are frequently used in the field of biostatistics.
PLO04 Bilgi - Kuramsal, Olgusal Knows the importance of ethical principles and ethical committees for the individual and society. Comprehends the importance of Biostatistician in ethics committees.
PLO05 Bilgi - Kuramsal, Olgusal He/She has advanced knowledge about statistical methods that are frequently used in studies in the field of health. 4
PLO06 Beceriler - Bilişsel, Uygulamalı Evaluates the knowledge in the field of biostatistics with a systematic approach
PLO07 Beceriler - Bilişsel, Uygulamalı Develops a new idea, method, design or application that brings innovation to the field of biostatistics, develops a known idea, method, design or application and applies it to a different field.
PLO08 Beceriler - Bilişsel, Uygulamalı Design, analyzes critically, interprets and reports observational and clinical researchs for new and complex problems in medicine and health sciences.
PLO09 Beceriler - Bilişsel, Uygulamalı He/She uses advanced statistical methods in the decision-making process in diagnosis and treatment in health sciences, and consults to researchers working in this field. 3
PLO10 Beceriler - Bilişsel, Uygulamalı Uses research and analysis methods that require high-level skills in studies related to the field of biostatistics. 4
PLO11 Beceriler - Bilişsel, Uygulamalı Develops and applies advanced statistical methods and techniques frequently used in health sciences at the level of expertise with original thought, research.
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Performs independently an original work that brings innovation to the field of biostatistics
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Performs advanced statistical analysis that can evaluate a scientific article.
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Develops the ability to read and write articles related to the field of biostatistics and apply for articles to national and/or international refereed journals.
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Takes an active role in solving original and interdisciplinary problems
PLO16 Yetkinlikler - Öğrenme Yetkinliği Develops new ideas and methods in the field of Biostatistics by using high-level mental processes such as creative and critical thinking, problem solving and decision making.
PLO17 Yetkinlikler - Öğrenme Yetkinliği Comprehends the ways to reach the evidence and evaluates the evidence critically.
PLO18 Yetkinlikler - Öğrenme Yetkinliği He/She determines the principles of lifelong learning and professional development as an attitude and displays this attitude in his/her works.
PLO19 Yetkinlikler - İletişim ve Sosyal Yetkinlik Understands the dynamics of social relations required by the health profession and critically evaluates and develops the norms that guide these relations.
PLO20 Yetkinlikler - İletişim ve Sosyal Yetkinlik Discusses the issues in the field with other experts in interdisciplinary studies, using effective communication skills, and provides academic consultancy by defending his/her original views.
PLO21 Yetkinlikler - İletişim ve Sosyal Yetkinlik Communicates written, verbal and visual with foreign language knowledge in international scientific environments
PLO22 Yetkinlikler - Alana Özgü Yetkinlik By using the knowledge of biostatistics and medical informatics, he/she contributes to the society's becoming an information society by presenting his/her knowledge and skills to his/her society.
PLO23 Yetkinlikler - Alana Özgü Yetkinlik Establishes functional interaction by defending original views in solving problems related to biostatistics
PLO24 Yetkinlikler - Alana Özgü Yetkinlik Consults using effective communication skills, takes part in teamwork in research, defends scientific ethical rules
PLO25 Yetkinlikler - Alana Özgü Yetkinlik He/She has the experience of working with other health disciplines as a requirement of the field.
PLO26 Yetkinlikler - Alana Özgü Yetkinlik He/she chooses and applies the correct statistical methods in his/her studies in the field of health and interprets them correctly. Performs advanced analysis and synthesis. 5
PLO27 Yetkinlikler - Alana Özgü Yetkinlik Uses current developments and information in the field of health for the benefit of society in line with the realities of the country.


Week Plan

Week Topic Preparation Methods
1 introduction to time series reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
2 Time series analysis and operations with time series reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Tartışma
3 Time series chart and conversions reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Soru-Cevap, Tartışma
4 Means in time series reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Tartışma
5 Creating models with time series reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
6 Model prediction with time series -I reading Öğretim Yöntemleri:
Anlatım
7 Model prediction with time series -II reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Tartışma, Soru-Cevap
8 Mid-Term Exam none Ölçme Yöntemleri:
Ödev
9 Model prediction with time series reading Öğretim Yöntemleri:
Soru-Cevap, Tartışma
10 Operations with stationary time series reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
11 Operations with non-stationary time series. -I reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
12 Operations with non-stationary time series. -II reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Soru-Cevap, Tartışma
13 Seasonal models reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Model predictions reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Tartışma, Soru-Cevap
15 Model analysis and model prediction reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Tartışma
16 Term Exams none Ölçme Yöntemleri:
Ödev
17 Term Exams none Ölçme Yöntemleri:
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 5 70
Assesment Related Works
Homeworks, Projects, Others 2 5 10
Mid-term Exams (Written, Oral, etc.) 1 18 18
Final Exam 1 30 30
Total Workload (Hour) 170
Total Workload / 25 (h) 6,80
ECTS 7 ECTS

Update Time: 29.11.2022 01:22