Many different approaches were taken to get results from the maps. The most common one was by using a trend line that compared the data and then looking at the R2 value of the trend line. This approach was used when comparing the Average Malaria 2004 – 2009 map to the tree cover, precipitation, average temperature, temperature related to P. falciparum, temperature related to P. vivax, herbal cover, elevation, and wetland percentage. The trend line approach was also used when comparing Malaria 2008 – 2009 to Hemoglobin SS Disease Allele Frequency 2009. The second comparison approach used was looking at the maps and data and trying to make visual comparisons. While this method is inaccurate and not a good way of telling whether there is any true correlation or not, it was the closest to being accurate for comparing Average Malaria 2004 – 2009 to the water ways and the Digital Elevation Model. The last way results were calculated was by using an ANOVA test. This test was conducted when comparing Average Malaria 2004 – 2009 and Ecoregion. All of the tests done by using a trend line turned up negative with an R2 value of less than 0.95 meaning there was no correlation between malaria and that part of the environment. While the visual comparisons are only estimates it did seem to show that, most of the time, rivers ran where there was a dense population of malaria which also means that malaria is higher where elevation is lower. The one test that did turn up the most significant data was with the ANOVA test. It showed that there was only a 1% chance that malaria was not related to the ecoregions and any value lower than 5% means there is a significant correlation.
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