Data Science And Statistical Modelling In Space And Time
Assessment – Report
Section C is a report consisting of spatial and temporal modelling. Instructions for the structure and contents of this report are given below. In general, R code should be included in an appendix.
This assessment is worth 50% of the module mark.
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You should submit a single pdf to the submission point.
C. Project [200 marks]
There are two files with data taken from a subset of the UK Met Office’s network of land surface measurement sites. These are:
1. metadata.csv This file contains site names, longitude, latitude and elevation for 20 locations throughout Britain;
2. MaxTemp.csv Maximum daily temperatures in degrees Celsius for the above sites for 2020 (note that this is a leap year, so there are 366 entries per site).
Perform an analysis of maximum temperatures in Britain in 2020, and write a report summarising the spatial and temporal variation, and the modelling that you carry out. Your report should provide a clear commentary of which models you are fitting and why, and any assumptions that you make, together with an assessment of how well any models you use perform in terms of model fit and predictive ability.
Within your report, you should provide modelling and answers for the following questions:
1. Fit a spatial model to predict the maximum temperature in Morecambe, Coventry and
Kinross on September 12th 2020;
2. Fit a time series model to predict the maximum temperature in Yeovilton on November
1st-7th 2020, and assess this model’s appropriateness for other locations.
3. Extend the analysis/modelling by considering your own question(s), going beyond these specific models, to better understand the spatial and temporal variability in maximum temperatures in Britain in 2020. At a minimum, your report should include a map of predicted temperatures and a map of uncertainties on a 0.1◦ grid over Britain.
The report should be no more than 8 pages (not including the appendix), with reasonable font size and readable figures, and have the following sections:
• Introduction – explaining the rationale behind the analysis, e.g. what questions are you aiming to answer;
• Initial Data Analysis – provide the reader with graphical and numerical summaries that highlight any spatial and temporal patterns, and possible outliers, within the data;
• Methods – describe the methods that you are going to use in your modelling, and justify why your choices are appropriate;
• Results – present the results of your analyses together with a clear narrative that will help the reader understand the results;
• Summary – summarise the key findings of your analysis, what were the answers to your questions? 1
• Bibliography – listing any papers and/or online sources that you reference in your report. • Appendix – R Code, extra plots, etc.
Plots that are important to the main narrative should be included in the main text. Supplementary plots (such as validation plots) may be included in the appendix, and referenced in the main text.
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