Question: Obtaining data samples from the dataset "HW 3 Dataset 1" (which will be sent in an email with that subject line), utilize any or all of the various regression model-fit assessment visual plots and/or graphs, results of statistical hypothesis tests, and numerical regression model accuracy measures, as well as any other applicable diagnostic tools available in R that we have discussed in the course thus far, to help identify and validate a linear regression model that appears to best fit the given data. These will likely include for example direct X-Y variable graphs and residuals vs. fitted value plots implemented in R. You will likely need to try a number of different response and/or predictor variable transformations, for example, using the diagnostic tools to decide which regression models appear consistent with the data and which do not. You should identify one or perhaps two candidate regression models that you believe are most consistent with the given data. Please try to include screenshots of the graphical plots you use as well as quote any relevant R code output. You can or even should include the R code itself as well if you feel it helps to support your argument. Please explain your reasoning as to why the model(s) you propose may be the right one(s) in plain natural language prose.

Price: $2.99

Solution: The downloadable solution consists of 5 pages
Deliverable: Word Document