2013/14 Undergraduate Module Catalogue

GEOG2115 Research project and statistical skills in physical geography

10 creditsClass Size: 40

Module manager: Prof Andy Baird
Email: a.j.baird@leeds.ac.uk

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2013/14

Pre-requisites

GEOG1070	Physical Geography Tutorial
GEOG1075	Data Analysis Skills for Physical Geography

This module is not approved as an Elective

Module summary

Excellent critical writing skills, numeracy (statistics and modelling), and an ability to design small research projects are the hallmark of a good geography graduate from a world top 50 university. This module aims to ensure all our graduates have these skills and that they know how and where/when to apply them in a variety of real-world situations.

Objectives

On successful completion of this module, students will have gained:
i. A detailed knowledge and understanding of how to design research projects in physical geography.
ii. Competence in the critical analysis of published studies by physical geographers and environmental scientists.
iii. A good level of numeracy (statistics and modelling) for the solving of physical geography problems.

Learning outcomes
Students successfully completing the module will be able to design their own research project (e.g., dissertation). They will also be able to identify effective strategies for data collection and analysis using a range of statistical and numerical methods, including factorial analysis of variance (ANOVA), multiple regression, and time series analysis.

Skills outcomes
On completion of this module students will be able to:
i. Write confidently and knowledgably on research approaches within physical geography.
ii. Demonstrate understanding of how to design a small research project in physical geography.
iii. Display competence in the use of a range of mulitvariate statistical methods, time-series analysis, and basic computer modelling.

Syllabus

i. Tutorials based around (a) reading of research papers in physical geography, (b) the design of example research projects, and (c) the design of a dissertation project.

ii. Research design and data analysis. Data analysis methods will include factorial ANOVA, multiple regression, and time-series analysis. Students will be provided with suitable data sets for practicals but will also be taught the principles of data collection.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	7	1.00	7.00
Practical	7	2.00	14.00
Tutorial	12	1.00	12.00
Private study hours			67.00
Total Contact hours			33.00
Total hours (100hr per 10 credits)			100.00

Private study

The statistics lectures will include follow-on reading material that students will be expected to complete in preparation for subsequent lectures and practical classes. Students will also have to prepare for tutorials (they will be set work involving reading of research papers, preparing reviews, and preparing presentations). Coursework preparation and completion will also be done in private study time as will revision for the statistics exam.

Opportunities for Formative Feedback

Student progress will be monitored via tutorial and practical class performance. Students will receive some feedback on their performance throughout the module via the marking of the two practicals. Students will complete two practice essays for the tutorials and these will be 'informally' marked and returned with detailed comments.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Research Proposal	1 x dissertation proposal (1500 words)	50.00
Practical	Statistics worksheet (~1500 words)	50.00
Total percentage (Assessment Coursework)		100.00

Re-sit information: If students do not attend the practical exercises they will be set an essay by way of re-sit. If they do attend, but fail or do not submit the practical coursework, they will be allowed to re-sit.

Reading list

The reading list is available from the Library website

Last updated: 23/04/2013

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