ASSIGNMENT: Research Skills & Statistical Methods
The following document outlines the format of a data analysis assignment for completion during autumn and spring terms. While the deadline is not until late in the spring term, you are advised to become familiar with the data, and to explore the assignment data each week, using any new techniques learned during each practical session. Every week of the course will include methods that could feasibly be used with the assignment data. By lecture 8 (Autumn week 9) and practical 7 (spring week 5), you will have been introduced to all of the necessary methods for completion of the assignment. Do not leave it to the last minute to do your analysis as much of it can be completed as you go along. You are encouraged to make use of practical time (particularly the optional help sessions) to ask any questions regarding the assignment. Also please make use of the statistics forum on the VLE (see slides from practical 1).
Deadline
Midday, Friday 22nd Feb (check with VLE for any last minute changes to date or hand-in instructions), online via the submission point on the VLE as a pdf document.
Aim
The aim of the assignment is to use methods in data exploration, presentation and statistical hypothesis testing to evaluate the implications of human activities for conservation management of IUCN Red-Listed grouper fish communities in a system of coral reefs.
Instructions
The data in the Excel file supplied together with this document are from a series of 21 coral reefs. The data have been gathered to determine the human impacts on IUCN Red-Listed grouper fish communities, relative to environmental influences. The data include one response variable (number of grouper fish species) and fifteen predictor variables, all of which are explained in the data file (note there are two worksheets in the data file; one including the data, and one including an explanation of the variables). As scientific researchers, your task is to use analytical methods taught during this module to analyse the data. From this you should determine the relative importance of the predictor variables for grouper fish ecology and for managing coral reefs. Useful recommendations for managers could include reef size and permissible human activities for grouper fish conservation.
Format of Report
The data should be summarised using single-spaced type in no more than 2000 words (i.e. around 4-5 sides of A4) in the style of a manuscript for submission to the Journal of Applied Ecology (2cm margin, ≥11pt font; see “author guidelines”, http://www.journalofappliedecology.org; but note that line numbers are not needed, and that figures and tables should be embedded within the text rather than presented at the end, including the following sections only:
– Methods (0.5 to 1 page, past tense): Summarise which statistical techniques were used and why, including introduction of the variables and any adjustments made. From this it should be clear how each analytical method contributes to the aim of the assignment. Abbreviations may be used, but they should be explained at first use. Tip: Before the main analysis, check carefully that any transformations performed have worked.
MSc Assignment – RSSM – Waters
– Results (about 1 to 2 pages, past tense): Present a summary of all data analyses including at least two figures and one table. This section should be succinct, with careful use of figures and tables to avoid large chunks of text and to highlight all of the results, with emphasis on the most interesting results. Include all necessary statistics to demonstrate the strength and direction of the observed differences/relationships. Figures and tables should be numbered, cited in the text and fully labelled so that they can be interpreted independently, including a detailed legend. Tip: The results will be interpreted in the Discussion section, so don’t draw any conclusions here.
– Discussion (about half to 1 page): Discuss the implications of the findings for grouper fish ecology and conservation, including recommendations for coral reef management. Pay particular attention to the limitations of the dataset – how reliable are the data for drawing conclusions? Consider the results in relation to existing literature. Make suggestions for future research that would improve on the analysis.
– References (