TÜRKÇE
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Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB251 |
| Name | Statistical Applications with Mathematica |
| Term | 2017-2018 Academic Year |
| 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 |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. GÜZİN YÜKSEL |
| Course Instructor |
Prof. Dr. GÜZİN YÜKSEL
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
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
Yok
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Validates a theorem using Mathematica. |
| LO02 | Uses in Mathematica interactive graphical visualisations. |
| LO03 | Computes in Mathematica using theoretical facts . |
| LO04 | Uses Mathematica to write scientific papers or master, doctor thesis etc. |
| LO05 | Uses the knowledge by using Mathematica documentation and other sources in the internet. |
| LO06 | Orders the facts about some software programs which are often used in Statistics and Mathematics. |
| LO07 | Simplifies the complex calculations by using software programs, to achieve results and to use of these. |
| LO08 | Orders the 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 Statistics | |
| 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 | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 4 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Make statistical inference (estimation, hypothesis tests etc.) | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques and gain insight | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programs | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | 4 |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | 2 |
| PLO14 | 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 | |
| PLO15 | 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 | |
| 2 | Basic numerical calculations and some mathematical functions in Mathematica | Reading source books-Application | |
| 3 | Defining variables and using the parenthesis | Reading source books-Application | |
| 4 | Symbolic computation and numerical computation | Reading source books-Application | |
| 5 | Defining functions and constants | Reading source books-Application | |
| 6 | Solving Equations and linear equation systems | Reading source books-Application | |
| 7 | Lists in Mathematica | Reading source books-Application | |
| 8 | Mid-term exam | Review the topics discussed in the lecture notes | |
| 9 | Lists in Mathematica | Reading source books-Application | |
| 10 | Basic plotting and defining plot options in Mathematica | Reading source books-Application | |
| 11 | Differentiation , Integration and Limits | Reading source books-Application | |
| 12 | Vectors , Matrices and Basic Matrix Operations in Mathematica | Reading source books-Application | |
| 13 | Descriptive statistics | Reading source books-Application | |
| 14 | Confidence intervals and hypothesis testing | Reading source books-Application | |
| 15 | Loops | Reading source books-Application | |
| 16 | Final exam | Review the topics discussed in the lecture notes | |
| 17 | Final exam | Review the topics discussed in the lecture notes |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
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 | ||