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In each assignment you will be able to earn up to 5 marks based on your engagement on the moodle Discussion forums from the topics associated with the given assignment. See the Assignment assessment criteria document for more details.
Question 2
Spinner dolphins are a small delphinid that reside in subtropical and tropical waters. I collected data on spinner dolphins in Fiji to explore characteristics of their whistles. The type of whistle (e.g., concave, constant, convex, downsweep, sine, and upsweep) along with a variety of other acoustic properties of individual whistles was measured and is summarised in the Spinner_dolphin data-set.
| Variable | Description |
| Whistle | Whistle classification (Concave, Constant, Convex,Downsweep, Sine or Upsweep) |
| Duration | The time span of the whistle (seconds) |
| Centre_Freq | The frequency recorded at the midpoint (centre) of the whistle (kHz) |
| Low_Freq | The lowest frequency recorded during a whistle(kHz) |
| Delta_Freq | The range in frequency recorded during a whistle(kHz) |
| Max_Freq | Maximum frequency (kHz) recorded during a whistle (kHz) |
| Range_50 | Centre frequency [minus] minimum frequency |
| Range_100 | Maximum frequency [minus] centre frequency |
| Inflections | Number of points of change in whistle curvature |
- Conduct an exploratory data analysis and present a summary of the Spinner_dolphin data-set.
- Find a low-dimensional representation of the numerical variables in the Spinner_dolphin data-set. Provide carefully labeled and well-formatted tables and/or figures as well as an informative summary of your model and results. In addition, provide a visualisation and brief summary of whistle type in the context of your low-dimensional representation.
Question 3 [15 marks]
The Pacific Islands region stretches from the eastern coast of Australia all the way to French Polynesia and is comprised of a wide variety of island countries and territories. Exploring the similarities and characteristics of these nations is useful for environmental management and planning. A summary of the variables contained in the Pacific_Islands data-set is listed below.
| Variable | Description |
| PICT | Pacific Island Country or Territory |
| Land_area | Total land area (km2) |
| Coastline | Total distance of coastlines (km) |
| EEZ | Economic Exclusive Zone area (km2) |
| Shelf_Area | Continental shelf area (km2) |
| Inshore_fishing_area | Continental shelf area accessible for inshore fishing (km2) |
| Coral_reefs | Percentage of the worlds coral reefs contained in this PICT |
| Seamounts | Percentage of the worlds seamounts contained in this PICT |
| Primary_production | Estimated primary production for the marine environment (mg of carbon/m2/day) |
| MPA | Marine protected areas (km2) |
| PA | Terrestrial protected areas (km2) |
| Pop | Population size of the PICT |
| Total_spp | Total number of animal species listed for thisPICT |
| Region | Melanesia, Polynesia or Micronesia |
- Use k-means clustering to identify the optimal number of clusters for the Pacific_Islands data-set. Visualise your results, provide some broad insights into cluster membership in relation to Region, and provide a brief summary of your results.
- Create at least two different types of dendrograms based on the Pacific_Islands data-set. Use PICT as your label on each leaf for these plots. Using the same number of clusters in each dendrogram compare and contrast your results. Provide a general interpretation of groupings seen in each of the dendrograms you produce.
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