This course is for business and economic students. It aims to be user friendly, with a minimum of mathematics and a maximum of explanation. The objective of this course is to help the students to describe the data in both graphical and numerical manner. This course also emphasis on data classification, summarisation, display and analysis in order to aid understanding. We illustrate that any decision-making process should be supported by some quantitative measures produced by the analysis of collected data.
Session 1: Introduction and descriptive statistics
Session 2: Probability, Contingency tables
Session 3: Normal distribution
Session 4: Confidence intervals
Session 5: Hypothesis testing
Session 6: Analysis of variance
Session 7: Index numbers
Session 8: Nonparametric methods
Session 9: Sampling methods
Session 10: Review
Course evaluation is based on a combination of Assigments, Group project and Final test as following
- 5 individual assignments: 30%
- 1 group project: 20%
- Final exam: 50%
- Aczel−Sounderpandian (2008), Complete Business Statistics, McGraw−Hill.
- Sonia Taylor (2018), Business Statistics For non-mathematicians a companion website at: https://www.macmillanihe.com/companion/Taylor-Business-Statistics/student-zone/
- Anderson D et all, Statistics for Business & Economics (2011), Cengate Learning
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Call For Applications 4 PhD Scholarships in Economics, Finance & Management
Applications Doctoral Programme in Economics (with integrated M.Sc. Economic Research)
Fully Funded PhD Scholarships in Economics and Business Administration
MRes/PhD Economics and Finance programmes
PhD Program in Finance at Swiss Finance Institute