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ABOUT THE AUTHOR:

Dr. Sivula has served as a graduate research methods professor and specializes in secondary analysis of data, ex-post-facto research, and evaluation studies. Early in his career he was a research team member for human performance and physiological testing. He has been avid outdoorsman for over forty years and is intrigued with the present scientific interest in Bigfoot. His current scientific interest in showing falsification of phenomena before ruling it out, by examining many possible or conceivable observations, while encouraging all types of kind of speculative theories. The current Bigfoot-Giganto hypothesis is among these.

ABSTRACT:

The purpose of this study was to examine selected geographical and environmental characteristics of regional “Bigfoot” incidence and sightings reports across the United States (lower 48). Secondary analysis of U.S. Census data matched against regional and state data of several hundred incidences and sighting reports (BFRO, 2005) were used for the selection of geographical and environmental characteristics. Results seem to suggest that relationships might exist between incidence/sightings and the following state characteristics: rural land in thousands of acres (r =.31*), number of farms in thousands of acres (r =.65**), farm acreage in millions (r =.31*), freshwater withdrawals of millions of gallons per day (r =.68**) and toxic chemicals in millions of pound released (r =.54**). The eleven "western states" have the highest incidence/sighting reports (M= 93), and also possessed the highest mean elevation (M = 4, 654 feet) and highest elevations M=13,300 feet) and lowest population per square mile at M= 49.2. With any ex-post-facto, secondary analysis of correlational data, there is always the possibility of the third variable problem (or spuriousness), where the presence of third variable explains the relationship of the other two. On the other hand, the large correlations of freshwater withdrawals (r = .68) and toxic chemicals in millions of pounds released per day (r = .68) are consistent with environmental conditions in many of the incidence/sightings reports (e.g. “foul smell in swampy areas”).

* p < .05 ** p < .01

Geographic Characteristics of Sasquatch Sightings In the United States

INTRODUCTION

Over the last decade sightings, loud vocalizations, and footprints of alleged creatures known as Sasquatches (Bigfoots) have been reported by eyewitnesses and the media throughout the United States. In January of 2003 the Discovery Channel hosted a scientific documentary investigating the sasquatch/Bigfoot phenomenon. Noted primate specialist Jane Goodall believes the animals exist. The Bigfoot Researchers Field Researchers (BFRO, 2005) database contains over 2000 incidents in the United States alone. Fahrenbach (1998) statistical analysis of sasquatch footprints yielded a normally distributed foot length, width, and heel width which seem to support the theory of a living population of animals, rather than a fictitiously created data or some figment of one’s imagination.

Bigfoot research is a very broad term used to describe any efforts to investigate, examine, probe or explain the reports and physical evidence associated with the Bigfoot phenomena (BFRO, 2005). Researchers seem to favor the Bigfoot-Giganto hypothesis. Ciochon et al. (1990) found jaw bones and over a thousand teeth (estimated age of 125,000 to 700,000 years) that they claim belong to Giantopithecus blacki, an extinct ape standing 10 feet tall and weighing 1,200 pounds. Bigfoot-Giganto theorists link the Giantopitheus blacki as possibly the ancestor to our Bigfoot. By walking upright and able to cope with temperate and mountaineous climates the Giantopitheus blacki might have crossed the Bering Land Bridge, which might enabled them to migrate to North America much like humans have been thought to have entered.

Based up Fahrenbach’s (1998) statistical analysis of footprints, and the hundreds of reports from various parts of the United States (BFRO, 2005), the patterns among the eyewitnesses are not demographic, i.e., they are not reported by certain types of people, rather they are geographic, reported by people who travel into certain areas and environments. Given these data sources and the premise that at least one population of a living entity exists, I am attempting to provide a statistical, geographic framework for further discussion. Qualitative analysis of hundreds of sightings and encounters provided a thematic analysis on which to further examine the environment and geography in which the Bigfoot is purported to exist. Sigthting in swampy areas, remotely wooded, mountaineous terrain, also with ample tree cover. They also seem to be more active in the night (some nocturnal tendencies), nomadic, and probably are in groups of two to four. With an estimated size of 8 to 9 feet, weighing 800 lbs. to 1000 lbs, Bourliere (1975) estimates that a mixed diet food consumption would be between 31 lbs. to 41 lbs. daily and also possibly several gallons of fresh water daily. So the basic premises of food, cover, and water foster this geographic inquiry.

I wish to state that this research and publication constitutes personal research and has in no way been aided, supported, financially or by other means by the academic institutions or which I am currently, or have been affliated.

METHODS

The report data were collected from two sources the Big Foot Field Researchers Association Database (BFRO, 2005) and the U.S. Census Bureau, Statistical Abstracts of the United States (2004-2005). The is an exploratory research design which looks for patterns, ideas, or hypotheses, rather than research that tries to confirm or test hypothesis. This secondary analysis and ex-post-facto design uses existing data rather than new data gathered for the study. The unit of analysis or cases are members of the 48 lower states which are grouped into the four major regions of the United States (Census, 2003) and the nine U.S. Standard Regions for Temperature and Precipitation (NCDC, 2001). The thought here is temperature and precipitation regimes largely determine the limits of practicality for water and agriculture resources. Livestock and crops depend on the availability of water, which is usually derived from watershed precipitation. Also, the heat tolerance of plants and animals determine what climates are favorable for different species.

Reports posted into the BFRO (2005) online database after September 2000 are assigned a classification. According to BFRO, these reports are analyzed, evaluated and investigated with techniques and approaches derived from the legal profession, law enforcement, and investigative journalism. BFRO states:
Class A reports involve clear sightings, in circumstances where misinterpretation or misidentification of other animals can be ruled out with greater confidence. There are few footprint cases that are very well documented. Those are considered Class A reports as well, because misidentification of common animals can be confidently ruled out, thus the potential for misinterpretation is very low. Credible reports where nothing was seen, but distinct and characteristic sounds of sasquatches were heard, are considered Class B reports, and never Class A, even in the most compelling "sound-only" cases. They are never Class A because the lack of a visual element raises the potential for a misidentification of the sounds.

ASSUMPTIONS AND LIMITATIONS

The first and foremost assumption of this study is that a living primate known as a Sasquatch or Bigfoot exists. Fahrenbach’s (1998) data extrapolations were also secondary in nature, with foot data collected for the most part in the Western States of the United States and the Western provinces of Canada (British Columbia and Alberta). Fahrenbach’s histograms on various foot dimensions suggest normality (presence of the bell shape curve), with skewness and kurtosis values near 0, from which one might infer that they are measuring a population of something. However, he states the data of his samples involved value judgements, aggregation of data samples, and some of the data might have been of the same creature. These are all sources of systematic and random error.

This study employs various secondary data sources (measured at different times) which in themselves have measurement error, and the incident reports are more of a phenomena occurrence than an actual sighting of some creature. Drawing a sample and employing sampling methods in the traditional sense in are almost futile sense we don’t know in reality that a population exists. Therefore, secondary analysis of various geographical and environmental attributes that might be associated with incidence reports provides a starting point for other research.

Parametric procedures allow us to analyze population parameters and are usually associated with variables which are based upon the assumptions that the observed data follow a normal distribution or the variances are equal. When these assumptions are violated non-parametric procedures are more appropriate and in cases where you data does not have exact values.
The need is evident for statistical procedures that allow us to process data of "low quality," from small samples, on variables about which very little is known (concerning their distribution). Specifically, nonparametric methods were developed to be used in cases when the researcher knows nothing about the parameters of the variable of interest in the population (hence the name nonparametric). In more technical terms, nonparametric methods do not rely on the estimation of parameters (such as the mean or the standard deviation) describing the distribution of the variable of interest in the population. Therefore, these methods are also sometimes (and more appropriately) called parameter-free methods or distribution-free methods. Parametric procedures assume that the underlying measurements are at least of interval, meaning that equally spaced intervals on the scale can be compared in a meaningful manner. However, in this study, this assumption is weak and probably not tenable, and the data rather represent a rank ordering of observations (ordinal) rather than precise measurements.

From the previous discussion a blend of parametric and non-parametric methods will be used to analyze the data where appropriate. Inferential statistics as a whole has the basic premise that a population exists, and a sample represents the given population. Fahrenbach’s (1998) previous research suggests a population might exist in the Western U.S. and the western provinces of Canada. Other than that possible population, other inferences would probably be a weak argument.

RESULTS AND DISCUSSION

Table 1 Frequency, Central Tendencies, and Standard Deviation of Sasquatch Incidence Reports of the Lower 48 States
(M = 47.6, Mdn = 26, S.E. = 10.04, and SD = 69.5)

State Incidence

Washington 347
California 303
Ohio 171
Oregon 171
Texas 140
Colorado 72
Florida 72
Pennsylvania 67
New York 63
Michigan 55
Arkansas 49
Oklahoma 45
Missouri 43
Indiana 42
Kentucky 40
Iowa 36
Tennessee 35
Illinois 34
Idaho 33
Louisiana 31
Alabama 30
Wisconsin 30
Utah 29
North Carolina 28
West Virginia 24
Maryland 23
Minnesota 23
Georgia 22
Kansas 21
South Carolina 21
Wyoming 21
New Jersey 19
Arizona 17
Montana 17
New Mexico 17
Virginia 16
Maine 13
Mississippi 12
South Dakota 11
New Hampshire 9
Massachusetts 8
Nebraska 7
Nevada 6
Vermont 4
Connecticut 3
North Dakota 3
Delaware 2
Rhode Island 2
Note: Data from BFRO as on 03-05

Table 1 displays the frequency of incidence reports in descending order. Washington (n = 347) and California (n = 303) both in western United States, as well as Oregon (n = 171). Texas (n = 171) represents the southern United States and the midwest is represented by Ohio (n = 171). The aforementioned states skew the mean value greatly (M = 47.6) when comparing it to the median value (Mdn = 26) which cuts the 48 states’ distribution in half. Here the median maybe more descriptive of the 48 states with “average” incidence reports at 26. The measure of dispersion (SD = 69.5 incidences) across the 48 states being once again affected by the five states with over 100 incidences per state. The standard error (S. E. = 10.04) estimate is usually an estimate of the population parameter, the smaller this value, the better the estimate of the sample mean is of the population mean.

Figure 1. Frequency of incidence across the 48 states with the distribution curve.
(click to view)

Figure 1 shows that the distribution is positively skewed (3.09) in which the infrequent scores are on the right of the histogram. The degree of peakness or kurtosis (10.05) is a measure to which observations cluster around a central point and usually shows he extent to which a distribution departs from the normal or bell shaped curve. In the theoretical normal distribution which again in theory represents a “normal population”, both the skewness and kurtosis values are zero. Consequently, one can readily observe we are not dealing with a normal population of incidence reports across the 48 states. More importantly, most parametric (population) statistical treatments of data analysis are usually somehow violated (e.g., normally distributed variable).
With this being said, further statistical analysis will also employ non-parametric procedures where appropriate.

TABLE 2C (click to view)

The subjective thematic analysis of the incidence reports on (BFRO, 2005) indicate that food sources, cover or forested lands, mountaineous areas, swamps, caves, caverns, and water seem to be most present in many of the incidence reports. Using the thematic analysis and present data available, Table 2 displays Sasquatch incident reports and selected geographical and environmental attributes that might be associated with sasquatch activity on a regional and state basis. The West land area is M = 106,779 square miles and also contains this region also contains most of the Sasquatch incident reports. The West has the smallest population per square mile (M = 49.2) of land area when compared to the other U.S regions. The regions’ highest points average (M = 13,300) feet, with the regions states’ averaging 4,654 in elevation. The West also has the largest number of freshwater withdrawls ( M = 10, 316) million gallons of water per day and the least amount of toxic chemicals in millions of pounds released at (M = 16.845 ) per year. Estimated wetland acreage is second in the U.S. regions averaging (M = 739, 831).

Table 2 (click to view)
Table 3 (click to view)

Table 3 displays the ANOVA of Sasquatch Incidence reports and selected geographic and environmental attributes that might be associated with sasquatch activity. Certainly there are violations of normal distribution and equal variance estimates, however, ANOVA may be the best estimate to use here due to the interval type data of the geopgraphic and environmental attributes. Sasquatch incident reports were not statistically significant at the ? = .05, with p = .076). Statistically significant regional differences on geographic and environmental variables were as follows: land area (p = .00), population per square mile (p = .00), highest point in feet (p = .00), approximate mean elevation in feet (p = .00), number of farms in thousands (p = .004), farm acreage in millions (p = .029), and wetland acre estimates (p = .019)

Table 2B displays the correlations and possible associations between geographic and environmental attributes and Sasquatch incidence reports. The subjective thematic analysis of the incidence reports on (BFRO, 2005) indicate that food sources, cover or forested lands, mountaineous areas, swamps, caves, caverns, and water seem to be most present in many of the incidence reports.

References

Bigfoot Field Researchers Organization (2005). Retrieved from: http://www.bfro.net/.
Ciochon, Russell L., Dolores R. Piperno, and Robert G. Thompson, 1990a. Opal phytoliths foundon the teeth of the extinct ape Gigantopithecus blacki: Implications for paleodietarystudies. Proceedings of the National Academy of Science, 87: 8120-8124.
Ciochon, Russel L., John Olsen, and Jamie James, 1990b. Other Origins: The Search for the Giant Ape in Human Prehistory. New York: Bantam Books.
National Climate Data Center (2001). U.S. Standard Regions for Temperature and Precipitation. Retrieved from: http://www.ncdc.gov/img/climate/research/2001/nov/usrgns_pg.gif.

U.S. Department of Agriculture, National Agricultural Statistics Service, Farms and Land in Farms, Final Estimates, 1998-2002 Table No. 797 (2005, March). Retrieved from: http://www.census.gov/prod/2004pubs/04statab/agricult.pdf.

U.S. Geological Survey, Estimated Use of Water in the United States in 2000, circular 1268. Table 356, Released (2004, March). Retrieved from: http://www.census.gov/prod/2004pubs/04statab/geo.pdf.

U. S. Environmental Protection Agency, Toxics Release Inventory, annual. Table 368. Released (2002, May). Retrieved from: http://www.census.gov/prod/2004pubs/04statab/geo.pdf.

U.S. Geological Survey, for highest and lowest points, Elevations and Distances in the United States, 1990. Table 351. (2005, March). Retrieved from: http://www.census.gov/prod/2004pubs/04statab/geo.pdf.

U. S. Deparment of Agriculture, National Resources and Conservation Service, and Iowa State University, Statistical Laboratory, Summary Report, 1997 National Resources Inventory, revised (2000, December). Retrieved from: http://www.census.gov/prod/2004pubs/04statab/geo.pdf.
Wetlands: Losses in the United States 1780’s to 1980’s (2005, March). Retrieved from: http://www.npwrc.usgs.gov/resource/othrdata/wetloss/table_1.htm.