Course Details

STATISTICS AND DATA ANALYSIS

DSBE511

Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1DSBE511STATISTICS AND DATA ANALYSIS3+0+037,5

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program DATA SCIENCE
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course Understanding the role of statistics in research and business practices.
Developing skills in data gathering and analysis.
Interpreting statistical results.
Course Content The focus of the course is on broad treatment of applications of statistics concentrating on techniques used in fields of business and economics. The course aims to focus on how to define, collect, organize, visualize and analyze data for a business problem by applying formal statistical techniques. Topics include descriptive statistics, parameter estimation, confidence intervals, hypothesis testing, analysis of variance and linear regression. In addition, course content includes computer implementations using available up-to-date statistical software.
Course Methods and Techniques powerpoint presentations to be presented in the course, practical applications with R and/or Stata programmes
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Eda Ustaoğlu
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Business Statistics: A First Course (Levine, D. M.; Szabat, K. A.; Stephan, D. F.)
Course notes were prepared based on the book i.e. Business Statistics: A First Course (Levine, D. M.; Szabat, K. A.; Stephan, D. F.)

Course Category
Social 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
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 40
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Araştırma Ödevi 1 20 20
Proje 1 30 30
Araştırma 1 10 10
Kişisel Çalışma 1 40 40
Yüz Yüze Ders 14 3 42
Total Work Load   Number of ECTS Credits 4,5 142

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Calculate descriptive statistics numerically and graphically.
2 Compute confidence intervals for unknown parameters of distributions.
3 Perform hypothesis testing with two samples.
4 Use linear, multiple regression models in data analysis.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Descriptive statistics
2 Sampling distributions
3 Point estimation of parameters
4 Statistical intervals and tests of hypotheses for a single sample
5 Statistical inference for two samples
6 Simple linear regression and correlation


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

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


https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=71467&lang=en