Enviro data analysis – Sea grass leaf length
Assignment Requirements
I have just copied in the instructions from the subject outline for you. I hope it makes sense. I will attach the excel spread sheet with the data. The first two tabs in the excel sheet are the summary so hopefully that’s all you need but there is other data there too.
Instructions:
This assignment requires you to design your own simple observational study, collect the data, analyse the data and write up it all up as a report. Include a title, your name, abstract, introduction, methods, results, discussion and references. To a great extent you can decide how sophisticated you want to get, but the analysis needs to be appropriate and rigorous AND the report needs to be accessible to an informed, but non- professional person. In other words, avoid jargon and don’t assume too much prior knowledge. Your study will compare the values of a variable from sets of data in this case the length of sea grass leaves compared to the time of year/season (Dec, Jan, Feb for summer, Mar, Apr, May for autumn, Jun, Jul, Aug for winter and Sep, Oct, Nov for spring). The seas grass is measured in cm and compared to the time of year. You will need to determine what statistical test will be needed to analyse the data. You will also need to check your data for normality and equality of variances, and transform your data if appropriate. Carry out your analyses, tabulate and/or graph your results and write up the report.
Note: you must include a statistical test in your report to pass. A report without a demonstrable statistical test will fail, no matter how well the rest of the report is written.
Relevant learning outcomes:
◦ have a comprehensive understanding of experimental design and observational studies in a range of contexts associated with environmental science
◦ have the ability to analyse and evaluate the utility of different types of data, how it is collected and analysed in order to make sound judgements about the quality of the research
◦ have the ability to generate simple models and hypothesise relevant to environmental problems and research
◦ have communication skills in exploring, interpreting, and presenting data graphically
◦ be able to undertake basic biostatistical analysis
◦ have the ability to interpret and communicate findings from environmental research clearly and coherently within a management context
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