Thursday, December 1, 2011

Abby Coker
Geometry Project 1
December 1, 2011
Fingerprint Statistics

I. Introduction

The complex and completely unique shapes on a person’s fingertips created by dermal papillae consist of geometrically formed patterns formed by ridge structures and pore configurations. While there are many different ways to classify fingerprints, this project deals with what scientists refer to as the level one classification system: large-scale pattern types. Nearly all fingerprints fall into four major categories: loops, whorls, arches, and accidentals (UCSMP Geometry). Loops are strongly curved patterns, the ends of which enter and exit the finger on the same side. Approximately 60% of all people have this type of fingerprint. Quite common as well, whorls (complete ovals) form 30% of the population’s fingerprints. However, only 5% of all people have arches, ridges that run across the fingers arching in the middle, or accidentals, a combination of two or more patterns. This particular project will statistically analyze and classify 20 different fingerprints to see if this data correspond to general percentages.

II. Explanation/Data

Using a piece of paper, graphite, and tape, 20 different fingerprints were gathered from the subjects’ right index fingers. Next, the fingerprints were classified according to the four major category types.

Number



Names

Fingerprint Pattern




Abby C.

Arches

2.



Audrey C.

Loops

3.



Lee C.

Arches

4.



Felicia C.

Loops

5.



Geneva B.

Accidental: Loops/Arches

6.



Wes C.

Loops

7.



Ross C.

Loops

8.



Jordan C.

Loops

9.



Zach C.

Loops

10.



Alex C.

Whorls

11.



Sarah K.

Whorls

12.



Brittany W.

Arches

13.



Katie B.

Loops

14.



Tom B.

Loops

15.



Sam B.

Arches

16.



Clark K.

Whorls

17.



LeAnn B.

Loops

18.



Joan R.

Accidentals: Loops/Arches

19.



Don R.

Loops

20.



Douglas C.

Loops


Using this data, the percentages for each fingerprint type were calculated. First, the number of each different type was divided by the total number of fingerprints gathered (20). This number was then multiplied by 100 in order to get the total percentage.

· Percentage of loops= (11/20) x 100% = 55%

· Percentage of whorls= (3/20) x 100% = 15%

· Percentage of arches= (4/20) x 100% = 20%

· Percentage of accidentals = (2/20) x 100% = 10%

The table below presents these percentages compared to the percentages of the general population.

Fingerprint Type

Number

Percentage

Average Percentage

Loops

11

55%

60%

Whorls

3

15%

30%

Arches

4

20%

5%

Accidentals

2

10%

5%


III. Conclusion

As inferred by the table above, the data gathered by this project does not perfectly align with general statistics. However, the overarching trends in the percentages do show similarities. For example, in both the percentages calculated in this project and the average percentages, loops were by far the most common fingerprint type. As expected, the accidental type of fingerprint was the least common. However, out of the 20 fingerprints gathered, whorls were 50% less common than expected. Likewise, people with arch fingerprints were 25 % more common than expected. Several possible reasons exist for these inconsistencies. First of all, according to the Scientific American Magazine, “There is an inheritable quality to fingerprints” (Langenburg). While “individual details” of the fingerprints are always unique, the “pattern types are often genetically inherited” (Langenburg). Therefore, this fact must be taken into consideration seeing as nearly all 20 fingerprint volunteers were related. Secondly, according to a study done by Scotland Yard the average percentages of general fingerprint types vary considerably depending on what finger and hand the fingerprint sample is taken from (DNA Handbook). However, the average percentage this project is based off does not specify which fingers or hands the fingerprints were gathered from. Thus, this could contribute to the statistical inconsistencies. Regardless of these discrepancies, completing this project helped me fully understand the fingerprint categorizing methods and allowed me to compare my relatives fingerprint trends to that of the general public.


Works Cited

"Patterns For Each Finger In Percentages ." DNA Handbook. n. page. Print. .

Geometry, University of Chicago School Mathematics Project, Benson, J., et. al, McGraw Hill, Chicago IL, 2009.

Langenburg,, Glenn. "Are one's fingerprints similar to those of his or her parents in any discernable way?." Scientific American . n. page. Print. .