ISB005 Mathematical Growth Models

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

Information

Code ISB005
Name Mathematical Growth Models
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal / Objective

Understanding and applying the mathematical tools used to model growth

Course Content

Types and uses of mathematical growth models

Course Precondition

none

Resources

Random growth models, Damron Mathematical models, Timbergen

Notes

Random growth models, Damron Mathematical models, Timbergen


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Make scientific research on Mathematics, Probability and Statistics.
LO02 They have the knowledge to make doctoral plans in the field of statistics.
LO03 Has comprehensive knowledge about analysis methods used in statistics
LO04 Has comprehensive knowledge aboutmodeling methods used in statistics
LO05 Comprehensive knowledge of methods used in statistics.
LO06 Indicates statistical problems, develops methods to solve.
LO07 Apply innovative methods to analyze statistical problems.
LO08 Designs and applies the problems faced in the field of analytical modeling and experimental researches.
LO09 Access to information and do research about the source.
LO10 Develops solution approaches in complex situations and takes responsibility.
LO11 It has the confidence to take responsibility.
LO12 He/She demonstrates that he is aware of his / her new and developing practices.
LO13 Transmits the processes and results of their studies clearly in written and oral form in national and international environments.
LO14 It considers the social, scientific and ethical values in the collection, processing, use, interpretation and announcement stages of data and in all professional activities.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Develops new methods and strategies in modeling statistical problems and generating problem-specific solutions. 4
PLO02 Bilgi - Kuramsal, Olgusal Can do detailed research on a specific subject in the field of statistics.
PLO03 Bilgi - Kuramsal, Olgusal Have a good command of statistical theory to contribute to the statistical literature.
PLO04 Bilgi - Kuramsal, Olgusal Can use the knowledge gained in the field of statistics in interdisciplinary studies. 3
PLO05 Yetkinlikler - Öğrenme Yetkinliği Can organize projects and events in the field of statistics.
PLO06 Yetkinlikler - Öğrenme Yetkinliği Can perform the stages of creating a project, executing it and reporting the results.
PLO07 Beceriler - Bilişsel, Uygulamalı Have the ability of scientific analysis.
PLO08 Bilgi - Kuramsal, Olgusal Can produce scientific publications in the field of statistics. 2
PLO09 Bilgi - Kuramsal, Olgusal Have analytical thinking skills. 3
PLO10 Yetkinlikler - Öğrenme Yetkinliği Can follow professional innovations and developments both at national and international level. 3
PLO11 Yetkinlikler - Öğrenme Yetkinliği Can follow statistical literature. 4
PLO12 Beceriler - Bilişsel, Uygulamalı Can improve his/her foreign language knowledge at the level of making publications and presentations in a foreign language.
PLO13 Bilgi - Kuramsal, Olgusal Can use information technologies at an advanced level.
PLO14 Bilgi - Kuramsal, Olgusal Have the ability to work individually and make independent decisions. 4
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have the qualities necessary for teamwork. 3
PLO16 Bilgi - Kuramsal, Olgusal Have a sense of professional and ethical responsibility. 2
PLO17 Bilgi - Kuramsal, Olgusal Acts in accordance with scientific ethical rules. 3


Week Plan

Week Topic Preparation Methods
1 What is growth reading related articles Öğretim Yöntemleri:
Anlatım
2 What does growth modeling mean? reading related articles Öğretim Yöntemleri:
Anlatım
3 Linear growth models? reading related articles Öğretim Yöntemleri:
Tartışma
4 Non-linear growth models reading the related article Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
5 Lojistic growth model reading the related articles Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
6 Weibull growth model reading the related articles Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
7 Richards reading the related articles Öğretim Yöntemleri:
Tartışma
8 Mid-term non Ölçme Yöntemleri:
Ödev
9 Gompertz reading the related articles Öğretim Yöntemleri:
Tartışma
10 Modified models reading the related articles Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
11 Heligman-pollard model reading the related articles Öğretim Yöntemleri:
Tartışma
12 Age pattern of mortality reading the related articles Öğretim Yöntemleri:
Tartışma, Anlatım
13 Comperative analysis reading the related articles Öğretim Yöntemleri:
Tartışma, Anlatım
14 Application of models reading the related articles Öğretim Yöntemleri:
Anlatım
15 Application of models 2 reading the related articles Öğretim Yöntemleri:
Alıştırma ve Uygulama
16 Final exam exam Ölçme Yöntemleri:
Yazılı Sınav
17 Final exam exam Ölçme Yöntemleri:
Yazılı Sınav


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

Update Time: 07.12.2022 01:14