| CODE | EMP5027 | ||||||||||||
| TITLE | Methods in Data Analysis and Quality Assurance | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Environmental Management and Planning | ||||||||||||
| DESCRIPTION | This study-unit will introduce students to data analysis and quality assurance skills. The first part of this study unit will introduce students to two widely-used data science languages and is intended to cater for students with no prior programming experience. Students will first be taught the basics of writing and running Python scripts. The basic syntax of Python will be introduced, including statements, variables, comments, conditionals and loops, lists, tuples and dictionaries, functions, and modules. Learning will be carried out through practical exercises and examples. Students will then be introduced to the basic syntax of SQL (Structured Query Language), including table creation, queries, relationships, and data updates and insertions. The second part of this study unit will introduce students to the application of Quality Assurance (QA) and Quality Control (QC) guidelines as applied to the whole environmental monitoring process, including sampling, data analysis, data interpretation and data management. The study unit will help students develop a system of documented procedures and plans to ensure that the environmental monitoring programme delivers data with known precision and bias. This will include personnel training programs, calibration procedures, written procedures and record keeping, followed by quality control activities to ensure that the QA process is functional and that the information collected is accurate, precise and properly recorded. Study-Unit Aims: - To make students aware of the utility and versatility of programming and query languages and their application in environmental monitoring; - To enable students to write simple code using Python and effectively work with databases using SQL; - To recognise the integral role of Quality Assurance and Quality Control activities within an environmental monitoring programme and be able to develop QA/QC procedures to be applied in practice. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Describe the basic features of the Python programming language and solve basic problems by writing programs in Python; - Describe what a database is and how it relates to SQL and build a database and query it; - Describe and analyse QA/QC activities as part of an environmental monitoring programme. 2. Skills: By the end of the study-unit the student will be able to: - Identify Python data types; - Write loops and decision statements in Python; - Write functions and pass arguments in Python; - Read and write files in Python; - Write SQL code to build database structures; - Update database content with SQL; - Use SQL to retrieve data with filter conditions and from multiple tables; - Participate in developing and managing a system of documented procedures and plans to ensure that the environmental monitoring programme delivers data with known precision and bias. Main Text/s and any supplementary readings: - WENTWORTH, P., ELKNER, J., DOWNEY, A.B. and MEYERS, C., 2012. How to Think Like a Computer Scientist: Learning with Python 3. Available online as an open source book: http://openbookproject.net/thinkcs/python/english3e/ - ZHANG, C., MUELLER, J. and MORTIMER, M., 2014. Quality Assurance & Quality Control of Environmental Field Samples. London: London: Future Science Ltd. (Available through UM Library Electronic Resources) |
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| STUDY-UNIT TYPE | Lecture, Seminar and Tutorial | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Belinda Gambin Adam Gauci Julian Mamo (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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