GV1DENNU: Data Environment

Module code: GV1DENNU

Module provider: Geography and Environmental Science; School of Archaeology, Geography and Environmental Science

Credits: 20

Level: Level 1 (Certificate)

When you'll be taught: Semester 2

Module convenor: Professor Andrew Wade, email: a.j.wade@reading.ac.uk

NUIST module lead: Buda Su, email: subd@nuist.edu.cn

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: Yes

Last updated: 20 May 2024

Overview

Module aims and purpose

The aim of this 20-credit module is to boost confidence in the use of maths and stats essential for geography and environmental science. This module will introduce the everyday maths needed to help plan, organize and do field and lab work, and the subsequent data analysis and interpretation. Students will be taught about selected statistical packages, their advantages and disadvantages, and how to make good charts to better understand and present the data collected. The module will not go into the detailed maths behind the statistical techniques, rather the emphasis will be on how to select the most appropriate statistical technique for the task in hand, and then learning how to use available software packages to apply that technique successfully. Data will be drawn a range of geography and environmental science case studies. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Demonstrate, through practical use, an understanding of essential mathematical concepts and techniques to support further study in environmental science. 
2. Choose the most appropriate statistical technique for common data situations found in environmental science. 
3. Include the choice of statistical technique in the design of a research project. 
4. Manage, analyse and visualise data using common software packages and be able to present data in graphical format. 

Module content

1. Re-arranging equations and substitution 
2. Scientific prefixes, notation, orders of magnitude and logarithms 
3. Descriptive statistics and plotting data 
4. Preparation is the key to success: experimental design starts with stats 
5. Comparing the means of two distributions: the t-test 
6. Comparing the means of more than two distributions: ANOVA 
7. Correlation, linear relationships and trends 
8. Non-parametric statistics 
9. Multi-variate statistics 
10. Group project: research design that includes stats 
11. Group project: research design that includes stats 
12. Group project: research design that includes stats 

Structure

Teaching and learning methods

Lecture based sessions to introduce the topics and case studies, followed up by computer-lab based practical-classes to use Excel and Minitab to make high-quality plots that are appropriate for the ata, and to learn and use different statistical techniques.

The final two weeks will focus on a group project, written up individually, that includes statistical analysis in research design.

Study hours

At least 35 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Formative on-line, multiple choice test. 

Reassessment

Additional costs