| CODE | EMP2020 | ||||||||||||||||
| TITLE | Statistics for Earth Systems Science | ||||||||||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | ||||||||||||||||
| MQF LEVEL | 5 | ||||||||||||||||
| ECTS CREDITS | 5 | ||||||||||||||||
| DEPARTMENT | Environmental Management and Planning | ||||||||||||||||
| DESCRIPTION | This study-unit will introduce students to basic statistical concepts, with an emphasis on practical application. Throughout, theory and methods of analysis will be extensively illustrated with examples relating to environmental datasets and through use of the R/RStudio software packages. Students will first be introduced to sampling design and sampling techniques, and to fundamental concepts relevant to statistical analysis, including different types of variables, probability, normality, and confidence. After this, students will explore how to obtain concise graphical and numerical descriptions of data obtained from observational or experimental studies. Students will also be introduced to inferential statistics, including significance tests (amongst which Chi-squared and t-tests) and to tests of correlation, as well as non-parametric alternatives. Students will also be introduced ANOVA and linear regression analysis. Study-Unit Aims: - Introduce students to the concept of sampling and enable them to understand the necessity of a careful sampling design; - Equip students with the skills necessary to be able to conduct descriptive and inferential statistical analysis of given data sets; - Make students aware of the important role of statistical analysis in research. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - Explain the elements of a reliable sampling design and strategy; - Use statistics appropriately when conducting a study or experiment; - Identify principles of good research design. 2. Skills By the end of the study-unit the student will be able to: - Collect data in relation to an identified problem, propose a related appropriate mathematical/statistical technique/model, and use this technique/model to solve the problem; - Test for reliability of data obtained; - Select appropriate statistical techniques for data analysis; - Apply mathematics and statistics to make predictions and inferences; - Derive, analyze and assess relationships between variables. Main Text/s and any supplementary readings: - Dytham, C. (2010). Choosing and Using Statistics: A Biologist’s guide (3rd Edition). Wiley – Blackwell Publishing. ISBN: 9781405198394. Not available, but available from e.g., https://wordery.com/choosing-and-using-statistics-calvin-dytham-9781405198394. - Gardener, M. (2017). Statistics for Ecologists Using R and Excel: Data collection, Exploration, Analysis and Presentation (2nd Edition, paperback). Pelagic Publishing. ISBN: 9781784271398. Available at the IES library (one copy). Also available as eBook: https://www.amazon.com/dp/B0759GNKVQ/ref=nosim?tag=pel0a-20 Suggested texts for further reading: - Crawley, M. (2014). Statistics: An introduction using R (2nd Edition). John Wiley & Sons Inc. ISBN: 9781118941096. Not available, but available from e.g., https://wordery.com/statistics-michael-j-crawley-9781118941096?cTrk=MjAzMzI1NzcxfDY1YzI0YWM0NzA4Yzg6MTo3Mjo2NWMyNDcyZWRmNzdjOC40OTY1NDU5MDpkZDA4ZTNlZQ%3D%3D - Dormann, C. (2019). Environmental Data Analsysi: An Introduction with Examples in R. Springer. DOI: https://doi.org/10.1007/978-3-030-55020-2 Reference text: - Jones, E.; Harden, H.; Crawley M.J. (2023). The R Book (3rd Edition). John Wiley & Sons Inc. ISBN: 9781119634324. Not available. An earlier version is available: https://www.cs.upc.edu/~robert/teaching/estadistica/TheRBook.pdf |
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| ADDITIONAL NOTES | Attendance to scheduled sessions (lectures, field work, seminar, laboratory sessions and any other teaching session in whatever mode) is obligatory and only students having a satisfactory attendance will be assessed in the study-unit. Students, who do not attend at least 85% of the teaching time allocated to the study-unit, will not be allowed to sit for any of the assessment components mentioned below. | ||||||||||||||||
| STUDY-UNIT TYPE | Lectures and Computer Lab Sessions | ||||||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Adam Gauci Mark Scerri (Co-ord.) |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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