All analyses and data exploration must be completed in R Programming Software. Section 1 The data below correspond to the measures of body length of 50 individuals of the Yellowfin

Tuna (Thunnus albacares), in metres. [20 marks] x <-c( 1.02, 0.99, 1.03, 1, 1.02, 0.98, 0.95, 1.04, 1.04, 0.91, 1.04, 0.91, 1, 0.98, 0.99, 1.05, 0.94, 0.99, 1.13, 0.93, 0.97, 1, 1.01, 0.97, 0.99, 1.05, 0.99, 1.01, 1.02, 1.02 ) Using the R programming software describe the variation observed in this dataset. That should be described in a sentence of text that includes a measure of central tendency, a measure of dispersion, and a figure (e.g. histogram, boxplot). In the rationale, explain why the measures you chose are reasonable choices for your particular data. [9 marks] [6 marks] [5 marks] SECTION FORMAT DETAILS YOU MUST INCLUDE Rationale R code and Output: Interpretation 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 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.