Statistics II

Learning Outcomes: 

1.Knowledge based
Experimental design and optimization

• Randomization and blocking
•  Two-way ANOVA
•  Latin squares and other designs
•  Interactions
•  Factorial versus one-at-a-time design
•  Factorial design and optimization
•  Optimization: basic principles and univariate methods
•  Optimization using the alternating variable search method
•  The method of steepest ascent
•  Simplex optimization
•  Simulated annealing
•  Time series analysis

2. Skills / Competences acquired

• Students will be able to design an experiment and analyze the data.

General Skills: 

Search, analysis and synthesis of data and information,
ICT Use
Working in an international environment
Working in an interdisciplinary environment
Project design and management
Critical thinking

Course Content:

•  Methods for constructing and analyzing designed experiments are considered.
•  Concepts of experimental unit, randomization, blocking, replication, and orthogonal contrasts are introduced.
•  Designs include completely randomized design, randomized complete block design, Latin squares design, split-plot design, repeated measures design, and factorial and fractional factorial designs.
•  Methods for analysis of environmental data are considered focusing in time series analysis.

Suggested Bibliography:

1. E-book « Statistics ΙΙ» Spyridon Rapsomanikis, available in the e-class.
2. J. N. Miller, J. C. Miller “Statistics and Chemometrics for Analytical Chemistry” Pearson Education, 2005
3. “Laboratory exercises”, G. Loupa, available in the e-class.