COURSE UNIT TITLE

Offered By

BUSINESS ADMINISTRATION (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR AYSUN KAPUÇUGIL IKIZ

Offered to

BUSINESS ADMINISTRATION (English)

Course Objective

The main purpose of this course is to discuss the role of business analytics in business administration; to conduct analyses in the scope of business analytics and business intelligence for discovering the related technologies and developing the right strategies to adopt in business.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

1.Textbooks

Pochiraju, B. & Seshadri,S. (2019). Essentials of Business Analytics: An Introduction to the Methodology and its Applications, Springer Cham. https://doi.org/10.1007/978-3-319-68837-4

2. Software and Coding Platforms (vary based on the accessibility conditions). Possible platforms:
MS Excel
Rapidminer
R, python
Power BI

Planned Learning Activities and Teaching Methods

* Lessons will be conducted with computer support.
* Theoretical sections will be supported with the relevant business cases. Basic applications will be developed by using a programming language and/or analysis environment. Regarding these applications, homeworks can be assigned to increase understanding.
* Each student will participate in a group project, and each project will cover a comprehensive application for a business problem.
* The projects will be submitted before the final exam.

Assessment Methods

Further Notes About Assessment Methods

1. Exams will evaluate the understanding of the theoretical background of business analytics and related applications in business.
2. Term project will be assessed based on the approaches and technologies in the proposed work and its alignment with the strategies related to business analytics.

Assessment Criteria

In this course, each student works on a term project as a team member. The term project aims to improve the students' problem-solving and written/oral communication skills. Students form their teams based on their preferences. The maximum number of team members is limited to 3.

The team is required to design a complete business analytics application using a company dataset (hypothetic or real). The instructor supplies datasets regarding specific companies, guidelines, and a template file for completing this project, and the students are informed about the project requirements.

The project work is requested to be completed by adhering to the following structural elements (including 18 traits in total):

* Introduction (10%) (company background, important factors affecting the primary variable in the problem)
* Data Preprocessing (15%) (Explore the data for identifying quality problems, Validate the data, Clean the data)
* Descriptive Analysis and Visualization (20%) (Numerical descriptive statistics -mean, median, standard deviation, minimum, maximum, percentiles; Visuals -Histograms, Bar charts, Boxplots, Cross-tabulations, Scatter plots with Correlation Analysis; investigate the patterns in data)
* Predictive Modeling I: Regression (20%) (Model Specification, Model Building, Diagnostics by residual analysis and improved model, Model Validation and Prediction)
* Predictive Modeling II: Logistic Regression (20%) (Model Specification, Model Building, Diagnostics by residual analysis and improved model, Model Validation and Prediction)
* Managerial Implications (5%) (explaining what the obtained predictions imply for the business and how these predictions can facilitate the decision making process.)
* The report quality of the term project (10%) (Assessed based on the following six traits: Logic & Organization, Language, Spelling and Grammar, Development of Ideas, Format.)

In project work, it is critical that all team members contribute together as well as provide quality content. The Peer Evaluation form is used to assess each team member's individual contribution by allowing them to evaluate both their own performance and that of other team members. Based on these peer evaluation scores, a multiplier coefficient is calculated to reflect each group member's contribution to the project. Therefore, students get their term project grade individually according to their contributions.

Language of Instruction

English

Course Policies and Rules

1. Plagiarism will result in disciplinary action.
2. It is compulsory to attend at least 70 % of the courses.
3. Assignments will not be accepted unless submitted on time.

Contact Details for the Lecturer(s)

DEU Faculty of Business
Department of Business Administration
Division of Quantitative Methods

Prof. Dr. Aysun KAPUCUGIL IKIZ
aysun.kapucugil@deu.edu.tr
Office No: 125/A
Office Phone #: 0.232.3018226

Assistant Instructor:
Berk Pişkin
berk.piskin@deu.edu.tr
Office No: 129

Office Hours

To be announced later

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes