EMP5027 - Methods in Data Analysis and Quality Assurance

MQF Level

Duration and Credits

Semester 1

5 ECTS

Mode of Study

Part-Time Day

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.

Method of Assessment

Assessment Component/s

Weighting

Project

40%

Project

60%

Main Reading List

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 今日黑料 Library Electronic Resources)

Need help?

Please check your eligibility to join this short course and time-tabling details with the Institute of Earth Systems. The short course will only be delivered subject to a minimum number of applications being received.

Information for International applicants

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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: Knowledge and 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.

Learning Outcomes: 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.

Non EU Applicants:

EUR425

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Micro-credentials offer the possibility of providing flexible learning pathways to respond to evolving needs and new developments, thus enabling students to tailor their studies to their needs. Micro-credentials may be combined or transferred into larger credentials, such as certificates, diplomas and degrees, provided that the relevant programme requirements are met. Applicants wishing to transfer micro-credentials to a programme of study are encouraged to seek the advice of the relevant academic entity.

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