All analyses and data exploration must be completed in R Programming Software. Section 2 [20 marks] Corals are sensitive organisms that live in a symbiotic relationship with tiny photosynthetic algae

called zooxanthellae. The zooxanthellae provide corals with oxygen and energy through photosynthesis, while the corals provide a habitat and nutrients for the algae. However, this interaction can be disrupted. When the water temperature rises beyond a certain threshold, corals may expel the zooxanthellae, leading to a loss of their vibrant colors. This expulsion is commonly referred to as coral bleaching. The loss of these algae not only affects the color of the coral but also deprives them of an essential energy source. While coral can recover from mild bleaching events if conditions return to normal quickly, severe or prolonged bleaching can result in coral death. The dataset below corresponds to water temperature in 20 sites across Eastern Australia, as well as the percentage of coral beds affected by bleaching. Use this dataset to test whether coral bleaching in this populations might have been associated with water temperature. Describe the results in a sentence (e.g. something you'd find in the results section of a paper), with the corresponding elements of the output obtained in R. In your rationale, make sure you indicate a justification of the method you used for your statistical test. temp <-c( 16.11, 17.02, 18.26, 16.72, 16.04, 16.68, 16.68, 15.72, 14.71, 17.7, 17.59, 16.57, 18.07, 16.91, 16.36, 16.46, 15.22, 18.57, 17.45, 18.86) perc_bl <-c( 59.44, 61.29, 64.74, 58.24, 59.64, 60.29, 60.44, 58.16, 54.02, 62.19, 62.52, 58.69, 64.86, 60.49, 58.95, 59.06, 56.77, 64.46, 62.18, 65.05 ) Rationale R code and Output: Interpretation [9 marks] [6 marks] [5 marks] SECTION FORMAT DETAILS YOU MUST INCLUDE In this section answer any questions asked and include the following points: 1. Rationale: Give a short narrative of why particular techniques (i.e. test or graph) were selected and the steps you took to get to the final analysis. Think about why were they appropriate for that dataset? This is expected to be a concise paragraph of 3-10 sentences. 2. Interpretation: Give an interpretation of the findings in the form of a short write up of the graphs and/or analysis in the format required for the results section of a scientific paper. Think about the correct presentation of graphs and statistical tests as you would see them in a paper. 3. R Code and output: Include all code that is used for the analyses/graphs etc. You can cut and paste directly from the console in R studio. However, you must not include unused code/output or codes that generated errors. If you do, it will be taken as an indication that you do not understand which line of code generated the outputs included and you will lose marks.