EEE5022 Applied StatisticsBahçeşehir UniversityDegree Programs CARTOON AND ANIMATIONGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
CARTOON AND ANIMATION
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE5022 Applied Statistics Fall 3 0 3 9
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Assoc. Prof. SAEID KARAMZADEH
Course Lecturer(s): Prof. Dr. SELİM ZAİM
Recommended Optional Program Components: none..........
Course Objectives: The course introduces fundamental topics in statistics and implements its applications to industrial, medical, financial, energy and similar type very large-size datasets to infer meaninful statistical results. The course is for gradute students with no significant background on this subject. Implementations will be performed on the open source statistical software R. Introduction to R programming will be given.

Learning Outcomes

The students who have succeeded in this course;
I. Identify basic terms in statistics.
II. Gain ability to use and apply basic methods and programming tools used in statistics over various engineering disciplines.
III. Ability to explore data and its relationships.
IV. Ability to perform hypothesis testing for statistical problems.
V. Perform statistical inference over statistical data.

Course Content

Topics include: Introduction to R programming, Sampling, Data Exploration, Exploring Relationships, Probability, Random Variables and Probability Distributions, Estimation, Hypothesis Testing, Statistical Inference, Multiple Testing Correction, ANOVA, Analysis of Categorical Variables, Regression Analysis, Bayesian Analysis, Survival Analysis, Over Representation Analysis, Meta Analysis.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction
2) Introduction to R statistical programming
3) Term Project
4) Data Exploration with R
5) Visualizing and Summarizing Relationships
6) Probability and Random Variables
7) Estimation in datasets
8) Hypothesis Testing for various engineering applications
9) Statistical Inference over various large datasets
10) ANOVA
11) Analysis of Categorical Variables
12) Regression and Bayesian Analysis
13) Survival analysis
14) Over Representation Analysis

Sources

Course Notes / Textbooks: Principles of Applied Statistics (Paperback), by D. R. Cox, Christl A. Donnelly 2011 ISBN-10: 1107644453 | ISBN-13: 978-1107644458
References: Introductory Statistics with R Peter Dalgaard 2011 ISBN 978-0-387-79053-4

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Project 1 % 30
Midterms 1 % 30
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 30
PERCENTAGE OF FINAL WORK % 70
Total % 100

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Study Hours Out of Class 14 42
Project 1 30
Midterms 1 40
Final 1 50
Total Workload 204

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) To have theoretical and practical knowledge and skills in cartoon and animation.
2) To be able to develop research, observation-experience, evaluation skills in the field of cartoon and animation and effectively communicate ideas, convincing actions and emotions using cartoon and animation and performance principles in every direction.
3) Making animated films with various artistic styles and techniques.
4) Designing the cartoon and animation production process using initiative, applying it with creativity and presenting it with personal style.
5) To be a team member in the production process of cartoon and animations, to be able to take responsibility and manage the team members under their responsibility and to lead them.
6) To be able to evaluate cartoon and animations in the framework of their knowledge and skills.
7) To be able to define and manage learning requirements in the field of cartoon and animation.
8) To be able to communicate with related organizations by sharing scientific and artistic works in cartoon and animation and to share information and skills in the field.
9) To monitor developments in the field of cartoon and animation using foreign languages ​​and to communicate with foreign colleagues.
10) To be able to use general information and communication technologies at advanced level with all kinds of technical tools and computer software used in cartoon and animations.
11) Using critical thinking skills and problem solving strategies in all aspects of development and production, effectively communicating ideas, emotions and intentions visually, verbally and in writing, and effectively incorporating technology in the development of cartoon and animation projects.
12) To have sufficient knowledge about ethical values ​​and universal values ​​in the field of cartoon and animation.