Learning outcomes of the curricular unit (knowledge, skills and competences to be developed by the students)
Knowledge of the concepts and principles of experimental design. Development of skills for the analysis of general and specific constraints to the onset and development of experiments and choice of methods for the analysis of results.
Syllabus
Types of experiments. Planning and design of experiments: definition of objectives and reference population; formulation of hypotheses to be tested; definition of variables, factors and levels of factors; choice of the number of replications and randomization. Accuracy and precision. Evaluation of resources for the management of an experiment, the performance of treatments and the collection of data. The linear model and the main types of experimental designs. Use of methods of uni- and multivariate statistical analysis.
Demonstration of the syllabus coherence with the curricular unit's learning objectives
The syllabus aims: at the conceptual level, to provide the ability to formulate strict and valid questions from the standpoint of the statistical model; at the management level of resources, to train the student in the literature research, in the interaction with peers and stakeholders and in the use of his/her own competences for making relevant decisions regarding the objective, materials and methods of an experiment; at the level of the analysis of results, to provide skills for the treatment of the results and their interpretation.
Teaching methodologies (including evaluation)
Teaching methods include theoretical sessions (face-to-face and distance), theoretical-practice sessions (face-to-face), tutorial guidance and seminars (face-to-face and remote).
The assessment consists of a theoretical-practical written final exam.
Partial or total exemption of final exam is possible. For this purpose, there are two theoretical-practice tests (PE1 and PE2) and a practical work (TR).
Part A = 15% TR + 35% PE1
Part B = 50% PE2
Getting a minimum score of 10 in any part, allows the exemption of final examination on the subject it evaluated.
The final score will be the arithmetic mean of the two parts.
Demonstration of the coherence between the teaching methodologies and the learning outcomes
The learning objectives lack theoretical exposure of the conceptual component, theoretical-practical interaction for the component of planning and analysis of data, seminars for case studies and tutorial support for autonomous work.
Bibliography (Mandatory resources)
Andersson, Oivind (2012). Experiment!: Planning, Implementing and Interpreting. New Jersey: Wiley, 288 pp Box, G.E.P., Hunter, J. S. & Hunter, W.G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed), New Jersey: John Wiley & Sons, 664 pp. Dytham, C. (2003). Choosing and Using Statistics - A Biologist's Guide (2nd ed.). Oxford: Blackwell Publishing, 249 pp. Hinkelmann, K. & Kempthorne, O. (2008). Design and Analysis of Experiments. Vol. 1 (2nd ed.). New Jersey: John Wiley & Sons, 631 pp. Hinkelmann, K. & Kempthorne, O. (2005). Design and Analysis of Experiments. Vol. 2. New Jersey: John Wiley & Sons, 780 pp. Moen, Ronald D., Nolan, Thomas W. & Provost, Lloyd P. (2012). Quality Improvement Through Planned Experimentation (3rd ed.). New York: McGraw-Hill Education, LLC., 512 pp. Ryan, T. P. (2007). Modern Experimental Design. New Jersey: John Wiley & Sons, 593 pp.
Observations
Teaching methodologies (evaluation included):
According to "Despacho n.º 16/2021" of the school's Board, theoretical classes in-room mode, including students up to the room's maximum capacity. In a weekly rotation mode, the rest of the students have access to theoretical classes by distance learning.
Practicals are in presence mode.
Periodical evaluations and exams are presential.
Attention: In case the Covid-19 pandemic worsens, there may be a reduction in the proportion of presential classes, or even a total substitution by distance learning.
