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By Craig Heinselman
44 Trailside Lane, Eastside Condo 17, Francestown, NH 03043 USA

An abridged version of the presentation and paper entitled Eastern Sasquatch Analysis: Potential Patterns or Dubious Data? Given at the 3rd Annual East Coast Bigfoot Researchers Meeting of September 22, 2001 in Delmont, Pennsylvania

Introduction:

Many theories exist as to what may represent the common term of Sasquatch or Bigfoot. Are they multiple species or sub-species? Do they differ in the eastern portion of the country from their western representatives? Such continual debates are often at the forefront of Hominology in North America. These
Debates, however intriguing, do not necessarily look at the raw data from a specific geographic area. This data is the core of this paper and corresponding talk.
In the western portion of North America a good deal of analysis has been performed on certain traits of reported Sasquatch. John Green has maintained an extensive database of national sightings from which he has offered rough statistics. George Gill in the late 1970's looked at selected cases for connections to ecological principles of Bergmann's Rule and Gloger's Rule. At the forefront is the contemporary work of Wolf H. Fahrenbach (see Appendix A).
In the eastern portion of North America little attention to data analysis has been demonstrated. Some isolated cases do exist, for example Don Keating and Paul Johnson have looked at height statures and sightings distributions of time. In general though, data analysis of eastern reports is rare.
Utilizing portions of all these various analyses, and related ones on mammalian species, it is the attempt then to see if a pattern does exist. And if so, what is that pattern per se.

Methodologies

654 total reports tying together one or more criteria are utilized in this study. The criteria evaluated are estimated height stature, estimated weight, coloration, foot length and foot width (assumed ball width when otherwise not noted by researchers). This data is taken from a variety of sources from around the country, from John Green's Sasquatch: The Apes Among Us, to John Bindernagel's North America's Great Ape: the Sasquatch, to self-published books and regional newsletters. The Internet is used sparingly, as reports are extremely easy to fabricate anonymously and have been done with this new tool of communication. Only sites tied to an established publication or from which contact information was obtainable for an interview is used.
These 654 reports are taken from 15 different states; Connecticut, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Vermont, Virginia and West Virginia were selected. These states are selected as they form a rough cutout of the country that share similar environments and atmospheric conditions. Bordering Canadian provinces are not included as for the sake of the analysis state boundaries and geographic locations from the United States are evaluated.
The analysis herein does not deal with certain behavioral or physical characteristics of reported Sasquatch outside of the selected criteria. This has been done to limit the variables initially looked at, but in an extended evaluation these variables would be necessary to determine more zoological and ecological behaviors of reported Sasquatch. The presence of 3 and 4 toes tracks do appear in cases in the east. These cases are not omitted, but amount to 3.7% of the overall data. When a separate analysis is run omitting these reports, the data variations amount to less than 1% from what is presented here.
It should not be taken that these 654 are the sum total of all reports from these areas, as they are not. 10%-100% or more reports from each state are known, however they did not necessarily meet the criteria requirements. The omission of reports for any reason unless as stipulated above or known as complete fabrications or hoaxes, would lead to an evaluator bias.
Te exclusion of various states may be viewed as a bias. However, to include all the states would be an immense undertaking. It is therefore necessary to separate states by rough geographies, as was the case here. Extended surveys, into other geographic regions and atmospheric zones would be invaluable in further understanding distributions and traits of.
Usage of an extended spreadsheet custom made in MS Excel as well as Visual SPC and PQ Systems Statistical Software is used to analyze the data. Data is collected from the years 1838-2001, with 91.89% from the last 50 years.

State Breakdown

Criteria Breakdown

* Track Length and Width do not necessarily coincide with sighting report, may be stand alone case
** Not one of the main criteria, however used for other purposes in analysis

Analysis of Data: Western to Eastern

Wolf H. Fahrenbach, in his report Sasquatch Size, Scaling and Statistics, uses a wide range sampling data from Alaska, Washington, Oregon, California, Idaho, Nevada, Montana, Utah, Wyoming, Colorado, and New Mexico. Additionally data from the Canadian Provinces of British Columbia and Alberta is used. The end result is 706 samples of foot length, 438 samples foot ball widths, 123 samples of foot heel widths and 89 samples of height stature and track length tied together. These far outreach the data from the east, but a comparison using the same methodology as Fahrenbach can be done to test for connection

*Comparison Data Height vs. Foot Length:

*Where foot length and height both reported in same instances

A 5% maximum difference is present when the data is compared side by side. This uniformity allows for continual comparative analysis to Fahrenbach's work. A relationship between the foot's length and width can be done to show if a symmetry appears between the west and east reports. The width of the foot divided by the length of the foot yields an index of .46 for the mean foot from the west and .45 for the east, or a 2.2% difference. A foot-to-height multiplier can also be extracted using Fahrenbach's report. The end comparison is a 5.84 multiplier for the west and a 5.71 multiplier for the east (using the mean values, this also equals a 2.2% difference west to east). These values can then be tied into a formula for estimating the height of a Sasquatch from a track.

The formula as presented by Fahrenbach is:

H = 29.624 L.42054 wherein the H is the height of the individual in inches, L is the length of foot in inches and a coefficient established from a plotted regression line of the values.

Fahrenbach doesn't demonstrate the inverse; however an estimation of the track length left by a reported Sasquatch can also be approximated by the inverse of the above formula.

L = (H / 29.624)2.37778 wherein L is the length of foot in inches, H is the height of the individual in inches and an inverted coefficient is utilized.

Utilizing the formula a track 21" long would have a height estimation for the Sasquatch at 8.8', a 12" track, yields a Sasquatch 7' in height, and so forth. There is a point to be made here though, this is but an estimation of the height of a Sasquatch as the raw data itself may be skewed one way or the other. Additionally sexual dimorphism may have some influence in the matter. As the information is based off a larger group a comparable percentage of male and female would theoretically be presented. Therefore as a rough guide this formula presented by Fahrenbach functions well. Even allowing for a percentage of error, the affect on the end result is a matter of a few inches. Wherein witness's description of height have a range, (i.e "It was 6 to 6 ? feet tall" or "It was 7 to 8 feet tall") this caution is justifiable.
Statistically 99.73% (using +/- 3 standard deviations) of the foot length will be between 5.2" and 26.2" (21" range). From Fahrenbach's data the western samplings fell within 6.3" - 24.9" (18.6" range). Overall this amounts to an 11.43% difference in range, with the eastern reports having a 2.4" larger range distribution statistically. Using +/- 3-standard deviations, 99.73% of the samples for height fall between 3.06' and 11.76' in the eastern study states.
A note of caution must be entered here. Usage of height statures is a fallible area. This information is relied on based off of witness descriptions. As witnesses may under or over estimate height, the distributions are not necessarily accurate. By taking a wider sampling, as is done here, the variation in descriptions is minimized. The data and equation derivatives that tie into height estimation therefore are strictly reference points only and should not be taken as incontrovertible fact.
Fahrenbach continues in his analysis to look at the gait of reported Sasquatch as evidenced by track finds, caloric intake requirements as well as life and growth cycles. These values are equally derived from mathematical adaptations based on primate and human characteristics. However, a duplication of these results for the east is not done at present for a variety of reasons. Chief among them is that this report is a preliminary investigation, and intended strictly as a manner to look at certain selected characteristics and ideas that are testable, for the most part, from the data with little supposition.
The data is indicative of a similarity in physicality and trace evidence regardless of geographic variations between eastern and western states.

What remains to be looked at is variation between set geographic states. These state boundaries, recognized by humans only, act as generalized distribution areas. Due in part to some study states having a higher level of researcher activity (Ohio, Pennsylvania and Maryland for example) the tendency is for a skewed regional look and a less accuracy in the end distributions. These tendencies make for interesting conversation, but do not make for strong statistical or trend data. One can extrapolate data from it, the end test though is verifying the data for accuracy with an increase in raw data to better balance of the state report differences.

The State Breakdown:

To minimize bias derived from inequality in state reports an acceptance and rejection of data fro analysis is done. In sampling, especially in a manufacturing environment, there is always the chance of faulty samples being included. A common practice in many industries is a sampling plan, particularly an older military one called MIL-STD-105E.
This standard breaks down the particular number of samples required from a batch in order to determine acceptance. In many industries a 2.5 A.Q.L. (Acceptable Quality Level) is a general default, there is a 95% confidence in acceptability of a batch following this sampling plan when using that A.Q.L. Tighter limits, 1.5, 1.0, .65 increase the confidence level while maintaining the same sampling base and only changing the acceptance/rejection points. For example a batch has 2000 pieces; a sample of 125 would be taken. If 7 were defective the batch would still pass, however if 8 were defective the batch would fail.
Using this same technique a rough acceptance of state data can be done. For example, a state with 2-8 reports needs 2 samples to be evaluated, 9-15 reports equals 3 samples, 16-25 reports equals 5 samples, 26-50 reports equals 8 samples, 51-90 reports equals 13 samples, 91-150 reports equals 20 samples, 151-280 reports needs 32 samples, 281-500 samples needs 50, and 501-1200 reports needs 80 samples. Taken as a whole the 654 reports looked at thus far meet the sampling requirements, with the exception of weight. The weight hence omitted as it is an argumentative attribute. Certain characteristics of the individual states do not meet these sampling procedures, which demonstrates a limited sampling area and more study is necessary.
This will limit the data used in further analysis; those characteristics that are rejected due to insufficient samples are not necessarily defective. Rather, they do not represent a valid basis for study. Color has been maintained though as all states maintained a minimum sampling acceptance level.
The only acceptable criteria to compare overall are the estimated height stature of the Sasquatch. By comparing median to mean (average) height statures from all states there is a slightly higher mean value than median, amounting to a 1.07% - 5.75% variation. This slight variation suggests that a mixed distribution of sexes and/or sexes is present; if the data was within 1-2% variation of each other it could be tied directly to witness variations in estimation, but with the larger range and some tests the data demonstrates a sexual and/or age variation as well.
Weight values as estimated by witnesses would have been necessary to omit even if they had not failed the sampling basis. The reason for this is best explained by looking at data from the famous Patterson-Gimlin Film, wherein weight estimates from data extrapolation have yield ranges typically between 300 and 1000 pounds, with extremes approaching 2000 pounds. Such wide ranges are evidence for a weak area of evaluation and as such are reminiscent of a side show carnival's Guess Your Weight booth.

Is there a Geographic Trend?

When plotted by increasing latitude, based off of each states capital for reference, there is no indication of increased height. Following the ecological principle, Bergmann's Rule, which states generally that as a species increase in latitudinal range an increase in body mass is observed, coupled with elevation and temperature influences, it is theoretically plausible that an increase in stature would be noted. George Gill in his study Population Clines of the North American Sasquatch as Evidenced by Track Lengths and Estimates Statures, dealt with this principle and others (see Appendix B. Latitudinal direction doesn't take into account is the elevation of an area, this elevation has been noted in other mammalian species to show an increase in body size. Regardless, the principle of Bergmann's Rule is a debatable topic in ecological thought even now after over 150 years of research, as the function that applies in some cases and not others is still far from understood.
From the data of the height estimates, and the progressive analysis of patterns in relation to geography, there is a tentative trend. As the elevation increases the height increase, as the longitude increase the height increases. Usage of the mean elevation is essential as plotting data against the highest or lowest elevation point within a given state will lead to skewed data.
What is shown is a tentative tie to the idea of Bergmann's Rule in that a species tends to increase in size with an elevation increase. Additional study of temperature and precipitation as well as other influences is required to correlate whether the two trends are connected or isolated instances or a fault of the data set utilized
Study comparisons in the future of variations in height as compared to longitude, latitude and mean elevation on a continental level , by generic region, would be beneficial to test this tentative trend.

Is There a Coloration Trend?

11 total color variations were found in the 367 reports. The combination of light and dark reports is required to get a better picture. This means that under the heading of DARK, the coloration of Brown, Black, Brown/Black, Dark, Reddish, and Reddish/Brown would be lumped. Under the heading of LIGHT, the coloration of White, Gray, Tan, Silver and Light would be lumped. Overall then DARK reports are substantially higher (81.23%) than LIGHT reports.
To represent the distribution of coloration it is not feasible to do so by the number of reports per state as this would show a large bias to states with more sightings. A single variable of light to dark is needed to fairly distribute the values within a state. The variable then is LIGHT divided by all color reports within a given state. The total variable for the 367 reports works out to .158 or 15.8% of sightings.
As some states do not have a value for the coloration variable, plotting all the information would cause skewed values. It is then necessary to omit states that lack a coloration variable. The data shows a miniscule increase trend of LIGHT coloration as the latitude increases, but a trend to the opposite as the longitude and elevation increase. This trend is opposite of what was seen in the height analysis by latitude, longitude and elevation. Consequently a scatter plat of the coloration variable against the height demonstrates that as the LIGHT variable increases the height decreases. If the inverse of the coloration variable is examined (i.e. 1 - Coloration Variable = Inverse Variable), no trend at all is present. This means that LIGHT coloration does exhibit a trend but the inverse, or DARK coloration, remains constant across all states.
This inverse connection demonstrates that there is little if any significant variation in coloration in the bulk of the states and what variation is seen would be a factor of individual variables of the Sasquatch itself and not a factor of the environment.
Extended survey into more humid and moist regions of the United States would be beneficial to determine if a trend is there in those regions.

Migration?

After looking at various data characteristics of height variation and coloration, it becomes necessary to evaluate whether Sasquatch in the east exhibit any form of migratory pattern as well as plausible range areas within their territories. If a population migrated it would be from either a latitudinal pattern or an elevation pattern.
Of the 654 reports looked at 549 (83.94%) of them have a specific month attributed to the report. This is a large amount of data to work with, if it is broken down in four approximate seasons, Spring, Summer, Fall and Winter the data is more manageable. These are approximate seasonal breakdowns only, as there is no set monthly start to a season of the year, rather they rely on astronomical factors of solstices and equinoxes which change slightly over time. Spring is defined as the months of April through June, Summer is defined as the months of July through September, Fall (Autumn) is defined as the months of October through December and Winter is defined as the months of January through March.
As some states have a larger number of sightings a bias for these states is created. To lessen this bias a variable is required. This variable, the seasonal percentile, is defined as the value of the number of sightings in a season divided by the total number of reports for a given state. Once this is done, then a latitudinal, longitudinal and mean elevation examination can be performed.
As the latitude increases an increased number of sightings occur in the spring, a leveling off in the summer, decrease in the fall and then an increase again in the winter. When the same data is plotted against a longitudinal direction, the opposite is seen. In the spring there is a decline, summer levels off, the fall shows an increase and the winter a decrease. When the data is plotted against mean elevation for the state there is no significant variation across the states during any of the seasons.
At this point the data supports that no significant large scale migration exists and that the Sasquatch remain essentially within their same theoretical home territory. If the data did support migration, it would be expected that the number of reports would be fewer in number in the northern latitudes during the winter months, and larger in number during those months in southern latitudes, or that plotted elevation changes would demonstrate an increase in reports in the warmer months within higher elevation areas and a decrease in reports during the cooler months from those same areas. None of these scenarios are demonstrated.

Summation:

1) Data comparison to western North America shows little variation indicating comparable height and other physical measurable characteristics.
2) There is a height increase in those states with higher mean elevations and those states with an increase longitude.
3) Light coloration marginal increases as the latitude increases and at the same time the height stature of reported Sasquatch decreases. By inverse the dark coloration remains stable across all states, indicating that any coloration variation is a factor of individual characteristic and not a factor of ecology.
4) No elevation or latitudinal migration exists.

Additional information regarding climatic conditions and individual state geographic variations may lead in the future to a more fine tuned analysis when coupled with extended sightings data from these areas. Physical characteristics as well have not been looked at, aside from coloration, extended analysis of behavioral and other physical traits would be an interesting and extensive undertaking and would be interesting to compare to correlations done by researchers across the country. Comparison for data variations in broader ranges is necessary to establish if any potential trend found is a true pattern and not a factor of sampling or of such miniscule proportions as to be variable over time.

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