This class exists in these courses :
• IÉSEG > IESEG Degree - Programme Grande École > Semester 2 > 2,00 ECTS

Prerequisites

It is essential that students have a background on Research Methodology.

Learning outcomes

At the end of the course, the student should be able to :
- prepare essential materials for preparing the final dissertation thesis.
- improve some skills and tools for analyzing data appear in various fields of management.
- realise the concept of decision making in an uncertain environment.
- understand the importance of describing data and summarizing descriptive relationships.
- define the descriptive Measures of central tendency and variability in data.
- use the general principles for analyzing data such as sampling, unbiasedness, estimation with confidence intervals and Tests of Hypothesis using MS Excel.

Course description

1.Concept of decision making in an uncertain business environment. Importance of data-driven business performance analysis.
2.Business Analytics and Data Visualization using Excel.
3.General principles for analyzing data: Pivot tables and hypothesis testing using Excel.
4.General principles for analyzing data: Estimation with confidence intervals and Tests of Hypothesis using Excel..
5. Simple Linear Regression and Multiple Regression and model building using Excel.
6.Categorical Data analysis using Excel and interpretting results.

Class type

Class structure

Teaching methods

• Case study
• Interactive class
• Project work
• Research
• Tutorial

Assessment

Students will learn how to use Excel in their dissertations and daily basis assesment will be done accordingly.
They will prepare a project and they will be assess by a final exam.

Recommended reading

• “Statistics for Business and Economics” by P. Newbold, W.L. Carlson, B. Thorne, Prentice Hal -

  Lecture notes and MS excel user guide

Internet resources

• IESEG Online