ISB251 Statistical Applications with Mathematica

3 ECTS - 2-0 Duration (T+A)- 3. Semester- 2 National Credit

Information

Code ISB251
Name Statistical Applications with Mathematica
Semester 3. Semester
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 3 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. GÜZİN YÜKSEL


Course Goal

The aim of this lecture is to introduce Mathematica Software program and to show how to to make applications of some basic lessons such as called Statistics, Calculus and differantial equations by using Mathematica for Statistics student.

Course Content

Introduction, listing, graphics, calculus, statistics.

Course Precondition

None

Resources

1. Enis Sınıksaran, Aylin Aktükün, Matematik ve İstatistik Uygulamalarıyla Mathematica, Türkmen Kitabevi,2009.

Notes

Course Notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 can learn the content of a theorem from a lecture or a seminar in the form which is useful for symbolic or numeric computations or graphical vizualization.
LO02 can use in Mathematica interactive graphical visualisations.
LO03 can compute in Mathematica using theoretical facts .
LO04 can use Mathematica to write scientific papers or master, doctor thesis etc.
LO05 can use the knowledge by using Mathematica documentation and other sources in the internet.
LO06 can learn about some software programs which are often used in Statistics and Mathematics.
LO07 Must be able to oversimplification of complex calculations by using software programs, to achieve results and to use of these.
LO08 Must be able to learn main issues of calculations by using computer applications ant to make an introduction to the programming


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 2
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 3
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 5
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.) 3
PLO10 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques 4
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
PLO14 Beceriler - Bilişsel, Uygulamalı Be aware of the interaction between the disciplines related to statistics 4
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 5
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 2
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


Week Plan

Week Topic Preparation Methods
1 An introduction the Mathematica software program Reading source books-Application Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
2 Basic numerical calculations and some mathematical functions in Mathematica Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
3 Defining variables and using the parenthesis Reading source books-Application Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
4 Symbolic computation and numerical computation Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
5 Defining functions and constants Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
6 Solving Equations and linear equation systems Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
7 Lists in Mathematica Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
8 Mid-Term Exam Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav
9 Lists in Mathematica II Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
10 Basic plotting and defining plot options in Mathematica Reading source books-Application Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
11 Differentiation , Integration and Limits Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
12 Vectors , Matrices and Basic Matrix Operations in Mathematica Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
13 Descriptive statistics Reading source books-Application Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
14 Confidence intervals and hypothesis testing Reading source books-Application Öğretim Yöntemleri:
Tartışma, Alıştırma ve Uygulama
15 Loops Reading source books-Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
16 Term Exams Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 2 28
Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 6 6
Final Exam 1 16 16
Total Workload (Hour) 78
Total Workload / 25 (h) 3,12
ECTS 3 ECTS