GST526 Statistical AnalysisIstanbul Okan UniversityDegree Programs Master of Arts in Gastronomy with thesisGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Master of Arts in Gastronomy with thesis
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

General course introduction information

Course Code: GST526
Course Name: Statistical Analysis
Course Semester: Spring
Fall
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 5
Language of instruction: TR
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: Department Elective
Course Level:
Master TR-NQF-HE:7. Master`s Degree QF-EHEA:Second Cycle EQF-LLL:7. Master`s Degree
Mode of Delivery:
Course Coordinator : Ar.Gör. MÜGE KAYA
Course Lecturer(s):
Course Assistants:

Course Objective and Content

Course Objectives: The aim of the course is to introduce students to basic statistical concepts, to teach data collection, organization, summarization, comparison and to introduce basic probability concepts and probability distributions.
Course Content: Basic Statistical Concepts: Definition of statistics, definition and types of units, qualification and elegant concepts, concept and types of variables. -Data collection, measurement, scaling, graphical presentation of data. -Measures of central tendency: Sensitive Averages (Arithmetic, Geometric, Squared and Harmonic Averages), Insensitive Averages (Mode, Median and other divisors). -Measures of Dispersion and Variability: Range of Variation, Range of Divisors, Mean Deviation, Standard deviation and variance, Coefficient of Variation and Standard value. -Moments: Moments with respect to origin and mean, standard variable moments. Skewness Kurtosis Measures: Pearson and Bowley coefficients, Skewness kurtosis measures based on moments.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Basic Statistical Concepts: Definition of statistics, unit definition and types, attribute and elegant concepts, variable concept and types
2) Basic Statistical Concepts: Definition of statistics, unit definition and types, attribute and elegant concepts, variable concept and types
3) Basic Statistical Concepts: Definition of statistics, unit definition and types, attribute and elegant concepts, variable concept and types
4) Data collection, measurement, scaling, graphical presentation of data
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) To be able to comprehend the basic concepts of social sciences, to be able to master the relationships between concepts in detail
1) To be able to reconcile economic and social phenomena with the theories in the field; to be able to follow the functioning of relations between people and societies
1) To be able to evaluate the information obtained in the learning process with cause and effect relationships; to be able to appreciate where, when and why information will be needed
1) To comprehend and express basic economic models analytically; to be able to project models from their outlines to their details
1) Be familiar with quantitative methods, logical reasoning processes and modeling techniques
1) To be able to have the ability to solve basic economic and social problems and to obtain the ability to analyze with detailed techniques
1) Acquiring knowledge about the economic and social environment, having the equipment to distinguish its functions and benefits
1) Ability to work effectively, self-confidence to take responsibility, self-confidence and entrepreneurial power by carrying the awareness of professional and ethical responsibility; to prioritize solidarity in teamwork Ability to use Turkish language effectively; to have knowledge of at least one foreign language for research
1) Measures of Dispersion and Variability: Range of Variation, Mean Deviation and variance, Coefficient of Variation and Standard value.
1) Indexes (Index types, fixed based simple index, different based simple index)
1) Conversion of the Current Price Series to Real Using Composite Indices, Price Indices
1) Sampling Concept and Sampling Methods
1) final exam

Sources

Course Notes / Textbooks:
References:

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

3

4

Program Outcomes
1) Ability to develop and deepen knowledge at the level of knowledge in the same or a different field, based on undergraduate level eligibility. Being able to comprehend the interdisciplinary interaction that the field spans. Ability to use theoretical and practical knowledge acquired in the field. Ability to interpret the knowledge gained in the field by integrating information from different disciplines and create new knowledge. Ability to solve field-related problems using research methods. Ability to carry out independently by combining field-related parts. To be able to systematically convey current developments in the field and one's own studies, in writing, verbally and visually, to groups within the field and outside the field, by supporting them with good and high-quality data.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Ability to develop and deepen knowledge at the level of knowledge in the same or a different field, based on undergraduate level eligibility. Being able to comprehend the interdisciplinary interaction that the field spans. Ability to use theoretical and practical knowledge acquired in the field. Ability to interpret the knowledge gained in the field by integrating information from different disciplines and create new knowledge. Ability to solve field-related problems using research methods. Ability to carry out independently by combining field-related parts. To be able to systematically convey current developments in the field and one's own studies, in writing, verbally and visually, to groups within the field and outside the field, by supporting them with good and high-quality data. 4

Learning Activity and Teaching Methods

Lesson
Homework

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Bilgisayar Destekli Sunum

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 1 % 10
Midterms 1 % 40
Final 1 % 50
total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Workload
Course Hours 15 30
Final 1 2
Total Workload 32