Course: Data Analysis and
Applied Statistics

Skills Developed

Being able to master all relevant statistical tools related to statistical quality control, process control and R&D in Food Science.

General Content

Tutorial class essentially, interactive lecture, problems, real case studies

• Basic Statistics: tables, charts
• Numerical descriptive measures
• Basic probabilities (events, Bayes, conditional)
• Discrete distributions (Binomial, Poisson, Hypergeometric…)
• Continuous Distributions (Normal, Fisher, Student…)
• Sampling
• Confidence Intervals (mean, proportion…)
• Hypothesis Testing
• Single and Multiple Sample tests (parametric and non parametric)
• ANOVA (one way, two ways, randomized block design)
• Post Hoc Tests (Tukey…)
• PCA, CA, HAC, MCA

Evaluation

Presentation of case study analyze in groups of 3 or 4 students.

• 50% written presentation (Power point)
• 50% oral presentation

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