Qualifying Data in Excel

There are a host of methods you can use to qualify the data. The methods will vary based on the type of data, how it was collected, and the type of modeling you are planning.

Sample Data (Points)

The first thing to do is read the FIA documentation on how the data was created and processed.

Question 1: Are there any issues with uncertianty mentioned in the documentation (spatial, temporal, or measurement)?

The next step is to look at the data in ArcMap.

Question 2: Is the data dispersed, random, or uniform?

Question 3: Does there appear to be any bias in the sampling?

Question 4: What is the typical distance between the points (you can use the "Near" tool for this if desired).

Load one of the datasets into Excel and create a histogram of the maximum heights and maximum diameters.

Question 5: What is the range on heights and maximum diameters?

Create scatter grams of height and maximum diameter against each predictor variable.

Question 6: Do you see anything that might indicate the data could be used to model potential distribution of Douglas-Fir trees? If so, what?

Predictor Variables

The predictor variables have been downloaded from the BioClim web site. Check the documentation for the data.

Question 7: Do you have any concerns modeling with this data?

Do a visual inspecition of the data in ArcMap by zooming in and panning around different areas to see if there are any surprises.

Question 8: Did you find anything?

Create histograms of each of the predictor variables.

Question 9: Are there any obvious grid patterns in the data that show up in a histogram?

Plot each of the predictor variables against each other.

Question 10: Do any of the predictor variables co-vary?

Turn-In

Answer each of the questions above. Include graphs and images to support your answers as appropriate.