This course aims to provide a review of methods for statistical inference, and develop an understanding of how these tools can be applied in a variety of business problems. The emphasis of this course would be on applications, through practical examples and cases. A variety of statistical software will be introduced. Topics covered include descriptive statistics, probability distributions, hypothesis testing, regression, design of experiments and analysis of variance.
Descriptive Analytics (BAN 827)
2021 Fall
Sabancı Business School
Business Analytics(BAN)
3
10
Selim Zaim selim.zaim@sabanciuniv.edu,
Click here to view.
Doctoral, Master
--
Click
here
to view.
| Programs\Type | Required | Core Elective | Area Elective |
| Business Analytics - Non Thesis | * |
CONTENT
PROGRAMME OUTCOMES
1. Develop the ability to use critical, analytical, and reflective thinking and reasoning 5
2. Reflect on social and ethical responsibilities in his/her professional life. 5
3. Gain experience and confidence in the dissemination of project/research outputs 4
4. Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments. 5
5. Communicate effectively by oral, written, graphical and technological means and have competency in English. 5
6. Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating. 4
1. Develop, interpret and use statistical analyses in decision making. 5
1. Demonstrated understanding of data-driven decision modeling and analysis concepts/frameworks. 5
2. Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models. 5
3. Ability to transform complex data into valuable insight and resulting value-adding actions. 5
4. Skills in hands-on data-mining tools and techniques. 5
5. Exposure to the analytical methods in basic business disciplines such as marketing, operations, and finance 5