Ce cours apparaît dans les formations suivantes :
• IÉSEG > MSc in Business Analysis & Consulting > Semester 1 > 6,00 ECTS

Pré requis

Basic knowledge of Excel (graphs, formulas…)
Basic statistical knowledge: scatter Plots, mean, standard deviation, linear correlation…
Reading statistical tables
Inferential Statistics: hypothesis testing, confidence interval on the mean..

Objectifs du cours

At the end of the course, the student should be able to :
- Breakdown a complex problem into smaller parts, especially when the problem is non trivial
- Formulate appropriate solution to solve each part of the conmplex problem: being able to select the relevant tools, select the right data, avoid mispresentation…
- Cross check data, identify outliers and solve missing data problems
- Collect relevant data using surveys and sampling methods
- Understand the importance of wording and variable description
- Propose creative solutions given the understanding of the data
- Master basic tools: correlation, box plot, distributions, payoff tables…
- Select the relevant method: Baye's analysis, confidence intervals, parametric and non parametric tests… and be able to check assumptions (normality…)
- Master expect knowledge tools and understand the new trends in analysis
- Analyze numerical and especially categorical data
- Demonstrate expertise in advanced tools and methods: SPC/SQC, Acceptance Sampling, Capability, Control charts, Decision Rules
- Link statistics with management methods and quality tools such as the six-Sigma
- Formulate, model and solve optimization problems
- Be open to new developments in their field of competence and be a reference point for those developments.
- Master a professional software

Contenu du cours

I Basics: Probabilities, discrete and continous distributions, sampling, confidence intervals
II Hypothesis Testing: assumptions, parametric and non parametric tests, independent and paired samples, categorical data
III Decision rules and decision making: payoff tables, decision trees
IV Quality tools: SQC, Tolerance, specification, lot acceptance sampling
V Process management: SPC, Capability, control charts, decision rules
VI Optimization methods: canonical, standard form, solver, sensitivity analysis
V Multivatiate analysis: FA, PCA, DA

Modalités d'enseignement

Organisation du cours

Méthodes pédagogiques

• Case study
• Coaching
• E-learning
• Interactive class

Évaluation

Assessment focusses on practical knowledge: the continuous assesment takes into account weekly case studies. The final exam is an open-book exam with a practical case.

Bibliographie

• Basic Business Statistics, 13rd Ed. Pearson, Berenson & all. (2013) -

• Operations Research: Applications and Algorithms. Wayne & all. -