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Here's where you lost me. You're basically saying that all reports in Minnesota and Iowa are hoaxes because they fall into group B. I disagree. (I don't care as much but the logic also applies to Michigan, Illinois, Ohio, and Wisconsin) While the methods you used might be sound, the data really needs to be adjusted. Here a few reasons I think the conclusions are off. 1. There are many encounters in Iowa that remain out of the public BFRO data base because they'd give up expedition locations. You'll see some of them when Finding Bigfoot Iowa gets aired. I can think of 7 or 8 encounters that happened while I was present, that would all be good enough to make it into the database (knocks, whoops with audio, and class B sightings which as shown in your report cannot really be attributed to black bear). In Minnesota, the BFRO presence has dropped off to form other groups that are taking reports and holding expeditions (one of which I am a part of). Reports that they receive don't make it into the BFRO database. When Finding Bigfoot rolled into Minnesota they looked to at least one of these other groups for potential locations and witnesses. 2. If your conclusions are somehow based on population, it needs some tweaking. The residents of Des Moines and Minneapolis/St Paul make up a large population percentage of both states, but the sightings are (generally) far away from those big cities. If you want to conclude that Des Moines and Minneapolis suburban sightings are hoaxes I can live with that. Take away those big cities and your population density for the rest of the state falls off greatly I'd suspect, and mostly likely changes the conclusions. (same argument for Illinois, Ohio, Michigan, and Wisconsin) 3. I think you somehow need to account for percentage of forest each state has. Iowa has more forest than you'd suspect, but I'd guess it's a pretty low percentage of total area compared to come other states. I'd like to know how the sightings per square mile of forest works out for all the states. (I may look into that actually) That might work in Iowa's favor but hurt Minnesota. 4. South Dakota as an A' while Iowa, Minnesota, Ohio, Illinois, and Wisconsin are all 'probable hoaxes' is a huge red flag. Sioux Falls must not be large enough. There's probably more and I don't have the know-how to figure out exactly how this all fits in. I just know the initial conclusions don't fit my view of reality. Edit: I left off rain totals, which I'm pretty certain matter greatly...

Short summary of my conclusions: Yukon Territory, Alaska, British Columbia, Northern California, Montana, Washington, Oregon, Manitoba, and Wyoming show multiple effects contributing to the Bigfoot phenomenon in these states. Hoaxing is present to a much higher degree here than in the rest of North America. Misidentification of black bears is another major contributor in these states. These two tendencies may be due to geographically-biased cultural effects (i.e., a general belief that this region is the "Bigfoot territory"). The remainder of the reports may be due to an uncataloged species. Idaho, Alberta, Colorado, New Mexico, Texas, Utah, Ontario, Oklahoma, Arkansas, South Dakota, Saskatchewan, Missouri, and Arizona are very interesting. Hoaxing here is only present at the same rate as in the remainder of North America. Misidentification of black bears does not contribute significantly to Bigfoot sighting reports in these states. Nearly all non-hoaxed reports here are likely due to an uncataloged species. The remainder of North America shows only contributions from hoaxing at this level of analysis. No correlations evidencing a contribution from sightings of animals, cataloged or uncataloged, were found in the data. One recommendation that comes from this research is that we should actually be devoting most of our efforts, insofar as report collection and analysis of specific details in reports are concerned, on the second set of states, outside of the "core" region consisting of the first set of states. This is due to a lower rate of hoaxing and absence of black bear misidentification. I hope to go deeper into this analysis in the coming weeks.

Attached is the promised paper detailing the updated statistical analysis I mentioned in my previous post in this thread. bigfootupdatedanalysispaper.pdf

Any given isolated report may be a hoax, or subject to any number of sources of error. A basic rule of empirical science is that you never draw any firm conclusions based on a single experiment or observation. Scientists strive for repetition and replication of experimental or observational results. Large sighting databases are valuable to Bigfoot research because they provide data in necessary quantities for drawing conclusions. The unique weakness of Bigfoot sighting databases, and "paranormal" data in general, is that we don't know to what degree the body of data has been tainted by heading or systematic misperception. This is where mathematical methods come into play. The best mathematical analysis of a Bigfoot sighting database that I am aware of is the analysis published by Glickman in 1998. The basic thrust of the method is that any person, in any place, at any time, is capable of submitting a hoaxes report. For this reason, the rate of hoaxing should be proportional to the human population. Similarly, if a Bigfoot sighting report is prompted by an encounter with an actual animal, then the more densely packed the people are in a given area, the more likely one or more of those people would be to encounter an animal residing within that area. Consequently, the rate of sighting reports of an actual animal should be proportional to the human population density. Using these two principles, Glickman analyzed the distribution of reports at the state level. He used a hierarchical cluster analysis (a method used to determine the similarity of individual pieces of data within a dataset) to divide the report database into two groups. Group A covered Alaska, Washington, Oregon, Northern California, Idaho, and Montana. Group B covered everything else. He found that in Group A, the number of reports per state showed a correlation with both the population and population density. The conclusion is that reports in these states are a result of a combination of hoaxing and actual animal sightings. On the other hand, Group B showed only a correlation with population, the conclusion being that reports in the rest of the country are solely due to hoaxing. In 2005 and 2006 I extended Glickman's analysis to check for correlations between the number of Bigfoot reports per state and the black and brown bear population densities in those states. There was no correlation with black bears in either Group A or B, and actually a negative correlation with brown bears in Group A. My conclusion was that we could eliminate the only two animals that could reasonably be mistaken for Bigfoot, and speculate that Bigfoot sightings really are due to an uncataloged animal species. Moreover, I concluded based on the brown bear data that Bigfoot and grizzly bears are natural enemies. Recently I've been updating all of these analyses based on the BFRO database instead of the outdated Green data that both Glickman and I had previously used. The BFRO database also allowed me to use Canada in the analysis. I should be finished with the analysis and write up shortly.