Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
-1MVU205Statistics3+0+03524.11.2024

 
Course Details
Language of Instruction Turkish
Level of Course Unit Associate Degree
Department / Program Accounting and Tax Applications
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To provide employees with the ability to collect, store, store and process the data they need in order to make the best decision in both enterprises and various organizations
Course Content It is aimed to teach definition of statistic, basic concepts, data and collection methods, regulation of data, central tendency measures, distribution measures, estimation theory, correlation analysis, regression analysis and indices.
Course Methods and Techniques Lecture, Question and Answer, Exercise and Example Solving
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Instructor Sakine Kurt Yiğitoğlu sakine.kurt@gedik.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Karacan Akademi Yayınları(2013), ''Temel İstatistik Kitabı''
Kazım Özdamar(2015), ''Paket Programlar ile İstatistiksel Veri Analizi'
Prof. Dr. Fikri Akdeniz (2022),''Olasılık ve İstatistik''
Course Notes Face to face, weekly notes will be taken during the lesson.

Course Category
Mathematics and Basic Sciences %60
Social Sciences %40

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 30
Quizzes 1 % 10
Final examination 1 % 60
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 3 42
Mid-terms 1 15 15
Final examination 1 25 25
Total Work Load   Number of ECTS Credits 5 124

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Collection of data to be used in the decision-making process
2 To make this data gathered in the operation to be regularized to the relevant persons and to display this data in various graphic media
3 Using central tendency and distribution measures to make decisions about which values ??the data group concentrates around and how it shows distribution characteristics
4 Determining the relationship between the variables used in the decision making process

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Definition of statistic, variables, main mass, unit, unit selection and data collection types
2 Series in statistics; Time, space and disintegration series, cumulative series, compound series and showing these series in graphic environment
3 Sensitive averages; Arithmetic mean, weighted arithmetic mean, geometric mean and squared mean
4 Non-sensitive averages; Mode and median
5 Change interval, standard deviation, coefficient of variation, variance
6 Estimation theory
7 Determination of significance levels of hypothesis tests
8 Chi-square test
9 Chi-square test Sample application exercises
10 Correlation analysis Regression analysis
11 Correlation analysis Regression analysis Sample application exercises
12 indexes
13 ndexes Sample application studies
14 General Repetition exam preparation studies

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13
All 4 5 2 2 4 4 3 2 2 2 2 2 2
C1 4 5 2 2 4 4 3 2 2 2 2 2 2
C2 4 5 2 2 4 4 3 2 2 2 2 2 2
C3 4 2 2 3 4 4 4 2 2 2 2 2 2
C4 3 5 5 2 4 4 3 2 2 2 2 2 2

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  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=113760&curProgID=57&lang=en