The xylem2data set contains xylem cavitationcounts of two woody species (A, B) in response to air temperature (15 to 35 degC) and elevation (low = L, mid = M, high = H). Build a Poisson GLM with...

The xylem2data set contains xylem cavitationcounts of two woody species (A, B) in response to air temperature (15 to 35 degC) and elevation (low = L, mid = M, high = H). Build a Poisson GLM with containing the three-way interactionbetween the explanatory variables. Check for overdispersion and take appropriate steps to deal with it if present. If the three-way interaction is statistically significant, follow up with apost-hoccomparison. If not, simplify the model using a backwards selection procedure based on likelihood ratio tests (i.e. remove non-significant terms until only significant terms remain in the model using a combination ofdrop1()and updated models). Check the model diagnostic plots and report on them. Plot the raw data in a multi-panel figure with one panel per elevation showing both species in each panel.Add the model fits incl. the 95% confidence intervals. You can use traditional graphics or ggplot2. When using traditional graphics, you should use thelayout()function to create a multi-panel figure with one panel per elevation showing both species together for each elevation.

Need to write up methods, result (including graph) and conclusion. Use microsoft word, include R code as supplements after the main test at the end of document.