A biologist is investigating how environmental factors relate to the size of a frog species. In a recent field trip, the biologist caught and measured the length (in mm) of 26 frogs. The collected data is stored within frogdata shown below, with data on altitude (meters above sea level) and the annual rainfall (in mm) for where each frog was caught. frogdata <- data.frame( len = c(26.7, 26.9, 26.4, 26.4, 25.2, 22.5, 26.5, 27.7, 26.3, 24.7, 24.3, 23.2, 25.1, 23.4, 22.3, 26.5, 26.0, 23.3, 24.4, 23.3, 24.2, 25.8, 23.4, 23.7, 29.6, 23.8), alt = c(600, 800, 1450, 1400, 100, 450, 400, 800, 800, 1100, 500, 400, 400, 850, 750, 900, 1400, 1000, 800, 750, 800, 350, 300, 750, 1050, 450), rain = c(1500, 1375, 1250, 1250, 1375, 1250, 1250, 1500, 1500, 1250, 1250, 1250, 1250, 1250, 1250, 1250, 1375, 1250, 1250, 1250, 1375, 1250, 1250, 1125, 1375, 1250) ) Fit a statistical model to the data and describe how frog lengths are related to altitude and average annual rainfall. Assess the quality of the fitted model. Are the modelling assumptions being satisfied or is there evidence of any of them being violated? Do you think that both explanatory variables are required for describing frog lengths, or perhaps one or both variables should be dropped? Explain your reasoning. Please submit a copy of your R code and any appropriate output (a photo/screenshot will be sufficient)