Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
3BUS 203Business Statistics I3+0+03514.01.2022

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Business Administration (English)
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The course aims to provide the students the ability to fully understand the basic facts and to be able to apply the common methods in statistics as a mathematical support tool in decision making in business administration
Course Content Basic concepts of statistics, distributions and their properties, distribution parameters, bivariate relationships, correlation and regression analysis ? cross table and contingency analysis
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. IRMAK UZUN BAYAR
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources

Course Category
Mathematics and Basic Sciences %100

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 % 25
Assignment 2 % 10
Attendance 14 % 5
Practice 1 % 0
Final examination 1 % 60
Total
19
% 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 5 70
Assignments 2 5 10
Mid-terms 1 10 10
Laboratory 1 3 3
Final examination 1 15 15
Total Work Load   Number of ECTS Credits 5 150

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Average student-Correctly uses the language of mathematics
2 - Is always aware of the validity of the carried out analysis
3 - Is able to prove the mathematical basis of the carried out analysis
4 - Represents the data using parameters and visuals with respect to the scale
5 - Correctly interprets the outcomes of analysis and comments on the validity, reliability and uncertainty of these outcomes

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to statistics, data and scales of measurement
2 Theoretical and empirical distributions, frequencies
3 Relative, cumulative frequencies, charts, graphs, tables
4 Descriptives, location parameters
5 Descriptives, dispersion parameters
6 Skewness , Kurtosis, Coefficient of Variance
7 Introduction to bivariate statistics, data types, graphs, tables
8 Midterm
9 Linear bivariate relationships, Covariance, Correlation
10 Least squares estimation, Simple Linear Regression, Coefficient of determination
11 Nonlinear relationships - Polynomial Regression
12 Nonlinear to linear transformations, nonlinear to polynomial transformations
13 Relationship in categorical data, contingency tables
14 Cross table analysis
15 Recitation
16 Final Exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1
C2 2 2 2
C3 3 3
C4 4 4 4
C5 5 5 5 5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
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