🇵🇹 PT

Objectives

At the end of the course Applied Statistics, the student should be able to:

  • Calculate location and dispersion measures interpreting their values
  • Interpret graphical representations of data according to the nature of the variables
  • Compute probabilities and probability distributions
  • Identify random variables and the most common probability distributions
  • Correctly apply statistical inference techniques
  • Use statistical methods for planning, control, interpretation and decision making in the context of engineering
  • Perform statistical analysis with the aid of statistical software

Program

  1. Population and sample. Data types and measurement scales. Descriptive Statistics.
  2. Probability concepts.
  3. Random variables and univariate probability distributions. Expected Value.
  4. Families of probability distributions.
  5. Parameter estimation.
  6. Confidence intervals.
  7. Hypothesis testing.
  8. Analysis of variance.
  9. Correlation and regression.
  10. Good fit tests for large samples.

Bibliography

  • Montgomery, D.C. and Runger, G.C. (2018). Applied Statistics and Probability for Engineers. 7th edition.
  • John Wiley. Devore, J.L. (2015) Probability and Statistics for Engineering and the Sciences. 9th Edition.
  • Brooks Cole. Guimarães, R.M.C. e Sarsfield Cabral, (2010) Estatística, Verlag Dashöfer Portugal
  • Pestana, M.H. and Gageiro, J.N. (2014), Análise de dados para ciências sociais: a complementaridade do SPSS, 6oEdição, Edições Sílabo.
  • Field, A. (2017), Discovering Statistics Using IBM SPSS Statistics. 5th Edition. London, UK: Sage.
  • Field, A., Miles, J., Field, Z. (2012), Discovering Statistics Using R. London, UK: Sage.

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