Learning goals (LG)

1. Understand concepts relative to exploratory data analysis

2. Understand the basis of sampling theory

3. Understand hypothesis testing procedures

4. Widen the concepts of correlation and regression to generalized linear models (GLM)

5. Recognize classification and ordination methods

6. Understand the use of questionnaires

7. Develop a framework for concepts related to reliability

8. Distinguish constant and variable failure modes

9. Identify typical survival curves

Skills

General (GS)

1. Team work

2. Search literature and write synthesis

3. Write a technical report

Specific (CSS)

1. Develop statistical reasoning

2. Suggest procedures for data treatment

3. Calculate sample size

4. Apply hypothesis testing

5. Calculate correlations, regressions and GLM

6. Apply classification and ordination methods

7. Analyze reliability of questionnaire scales

8. Simulate random variables used in reliability

9. Calculate and discuss reliability and maintenance

1. Exploratory data analysis

Distributions and tables

Statistics and charts

2. Sampling

Confidence intervals

Number of samples and error margin

3. Hypothesis testing

Comparison of two or k samples

Parametric and non-parametric tests

4. Correlation, regression and GLM

Correlation and simple linear regression

Multiple regression

GLM

Maximum likelihood

Hierarquical models

5. Classification and ordination methods

Cluster analysis

Discriminant analysis

Principal component analysis

6. Questionnaires

Structure of a questionnaire

Scale validation

7. The concept of reliability

Different aspects of reliability

Reliability and statistics

8. Random variables

Fundamentals

Negative exponential and Weibull distributions

9. Equipment association

Block diagramme

Configurations and redundancy

10. Human reliability

Human errors, consequences and categories

Error versus verification/inspection costs

11. Availability of repairable systems

Availability and maintenance

Failure and repair rates

This subject is organized in two parts, Statistics (20 h) and Reliability (25 h). Lectures are used to introduce learning themes. Concepts and definitions are presented succinctly. Teaching of statistics recipes is avoided, but concrete application of tools and simulations is favored. Examples are explored and problems are solved in order to consolidate knowledge and to develop skills. Classes occur in a computer room and tutorial files with instructions are used as well as data files and files with expected results. Assessment includes answering an individual questionnaire about reliability and the writing of a report (groups of 1-3 students) about statistics, aiming to develop and assess several skills (GS1-GS3). The questionnaire includes all reliability topics and some of the taught examples. In the report, three of the taught themes are developed.

Afonso, A. & C. Nunes (2011). Estatística e probabilidades: aplicações e soluções em SPSS. Escolar Editora,

Lisboa, 554 pp.

Gotelli, N. J. & A. M. Ellison (2004). A primer of Ecological Statistics. Sinauer Associates, Inc., Sunderland, 510 pp.

Heeringa, S. G., B. T. West, P. A. Berglund (2010). Applied survey data analysis. Chapman & Hall/CRC, Boca Raton,

FL, 467 pp.

Hill, M. M., A. Hill (2009) Investigação por questionário, 2ª ed. Edições Sílabo, Lisboa, 377 pp.

Oliveira AG (2008) Bioestatística, Epidemiologia e Investigação. Teoria e Aplicações. LIDEL, Lisboa, 255 pp.

Qian S.S. (2010) Environmental and ecological statistics with R. Chapman & Hall/CRC, Boca Raton, 421 pp.

Reis E (2001) Estatística multivariada aplicada. 2ª Edição. Edições Sílabo, Lisboa.

Smith, David J. (2011) Reliability, maintainability and risk: practical methods for engineers, 8th ed. Elsevier, Amsterdam, 440 p.

Zuur A.F., E.N. Ieno & G.M. Smith (2007) Analysing ecological data. Springer, New York, 672 pp.

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**Teóricas**- 35 hours