Class Data analysis in environment

The Data Analysis in the Environment course is part of the field of Environmental Engineering and focuses on the application of statistical methods and calculations to interpret environmental data. It covers the collection and processing of data from public sources, exploratory analysis, calculation of descriptive and inferential statistics, modeling, and interpretation of time series. The course enables students to transform environmental data into relevant information for environmental management, monitoring, and sustainable decision-making, integrating theoretical knowledge and the practical application of quantitative methods.

Not applicable

1. Introduction to Environmental Data Analysis: Concepts, types of data, quality, and importance of statistics. 2. Descriptive Statistics: Measures of central tendency and dispersion, histograms, boxplots, correlation. 3. Public Databases: Data collection and processing (Copernicus, INE, NOAA) for analysis. 4. Time Series: Decomposition, trends, seasonality, autocorrelation, and interpretation. 5. Inferential Statistics: Hypothesis testing, regression, ANOVA, and confidence intervals. 6. Modeling and Forecasting: Simple statistical models, parameter estimation, trend forecasting. 7. Visualization and Communication: Graphs, tables, and clear presentation of results. 8. Case Studies: Application to pollution, climate, water resources, and biodiversity.

The course combines theoretical classes with practical exercises involving step-by-step statistical calculations, interpretation of results, and time series analysis. Students work with real data, apply statistical calculation methods (averages, deviations, regressions, ANOVA), and discuss the results in collaborative work and case studies, promoting critical thinking, autonomy, and the ability to communicate quantitative conclusions.

Davis, J. D. (2023). Introduction to environmental data science. Chapman & Hall/CRC. Pedrosa, A. C., & Gama, S. M. A. (2016). Introdução computacional à probabilidade e estatística (3ª ed.). Porto Editora. ISBN 978¿972¿0¿01990¿5. Murteira, B., & Antunes, M. (2013). Probabilidades e estatística (Vols. I & II). Escolar Editora. Montgomery, D. C. (2012). Statistical quality control (7th ed.). John Wiley & Sons. ISBN 9781118146811 Le, N. D., & Zidek, J. V. (2006). Statistical analysis of environmental space-time processes. Springer. Brown, L. C., & Berthouex, P. M. (2002). Statistics for environmental engineers (2nd ed.). CRC Press. ISBN 9781566705929