Department: DCET
Scientific area: Mathematics
Total contact time: 35
In this course are introduced the concepts and fundamental techniques of statistical analysis and statistical inference, and demonstrated their usefulness to solve problems in the area of Food Science.
Analysis of Variance
Linear Regression
SPSS
Statistical Inference
- Characterize, distinguish and apply some of the techniques of descriptive statistics;
- Apply and interpret some methods of Parametric and Non-Parametric Inference,
- Analysis of Variance (ANOVA) and
- Linear Regression.
2. Parametric Hypothesis Tests: t-student test (independent and paired samples), variance ratio;
3. Non-Parametric Hypothesis Tests: Chi-square test; Kruskal-Wallis test; Wilcoxon test; Kolmogorov-Smirnov test;
4. Analysis of Variance (ANOVA);
5. Linear Regression.
All topics of the program will be given in a practical perspective, always accompanied with the use of SPSS software for the implementation of the different methods and interpretation of statistical tests in practical examples.
Recommended:
• T. A. Oliveira (2004), Estatística Aplicada, Universidade Aberta
• Pereira, A. (2013) SPSS, Guia Prático de Utilização, Edições Sílabo, Lisboa
Complementary:
• Reis, E., Calapez T. Estatística Aplicada, Edições Silabo, Volumes I e II
• Marôco, J. (2014) Análise Estatística com o SPSS Statistics, Edições Sílabo, Lisboa.
• Campos Guimarães, R. e Sarsfield Cabral, J.A. (2011), Estatística. Lisboa, Portugal, Verlag Dashofer.
• Tyrrell, S. (2009), SPSS: Stats Practically Short and Simple; BookBoon.com (ebook)
E-learning
Evaluation is made on individual basis and it involves the coexistence of two modes: continuous assessment (60%) and final evaluation (40%). Further information is detailed in the Learning Agreement of the course unit.