Course Details

BUSINESS STATISTICS 2

BA222

Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
4BA222BUSINESS STATISTICS 23+0+035

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program BUSINESS ADMINISTRATION
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course To understand the role of statistics in research and business practice
To develop skills in data gathering and analysis
To interpret statistical results
To obtain sufficient background to support further studies in business applications
Course Content The focus is on broad treatment of applications of statistics, concentrating on techniques used in business. This course aims to focus on how to define, collect, organize, visulize and analyze the data for a business problem by applying statistical techniques. Topics include descriptive statistics, parameter estimation, confidence intervals, hypothesis testing, analysis of variance, and linear regression. The course includes computer implementations using available up-to-date statistical software.
Course Methods and Techniques TBA
Prerequisites and co-requisities ( BA223 )
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Eda Ustaoglu eda.ustaoglu@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Business statistics: A first course, Levine, D. M., Szabat, K. A., & Stephan, D. (2020) 8th Global Edition. Pearson.
Course rotes were prepared using the book: "Business statistics: A first course, Levine, D. M., Szabat, K. A., & Stephan, D. (2020) 8th Global Edition. Pearson."
3
2

Course Category
Field %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
Quiz/Küçük Sınav 1 % 35
Ödev 3 % 15
Final examination 1 % 40
Diğer (Staj vb.) 1 % 10
Total
6
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Belirsiz 10 5 50
Yazılı Sınav 1 40 40
Sunum 3 2 6
Soru Çözümü 5 2 10
Final Sınavı 1 40 40
Total Work Load   Number of ECTS Credits 5 146

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 do descriptive statistics (summarize data numerically and graphically),
2 calculate point estimates for unknown parameters of distributions,
3 compute confidence intervals for unknown parameters of distributions
4 perform hypothesis testing with two samples,
5 construct and interpret linear , multiple regression models
6 use a statistical software (preferably MATLAB, Python, Minitab) to carry out the above.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction
2 Confidence interval estimation
3 Confidence interval estimation
4 Fundamentals of hypothesis testing
5 Fundamentals of hypothesis testing
6 Two sample tests and one-way ANOVA
7 LFW
8 Review and midterm exam
9 Chi square tests
10 Chi square tests
11 Simple linear regression
12 Simple linear regression
13 Multiple linear regression
14 Multiple linear regression


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
All 3 4 3 2 3 2 2 1 1 2
C1 3 1 5 4 5 4 1 1 2 1
C2 5 3 2 4 2 5 5 2 1 1
C3 5 4 2 5 2 4 5 1 3 1
C4 3 4 2 2 1 3 5 1 3 5
C5 2 1 2 2 1 3 4 2 2 5
C6 3 4 3 2 5 1 1 2 1 1

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


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=70552&lang=en