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Statistical Validity of Environmentally Variable Small Population Data Bases

CSEF · 2005 Mathematics & Software

Ariana G. Haro · Bloomington Middle School, Bloomington

Overview

Objectives/Goals The goal was to determine whether a particular area surveyed statiscally represents the slightly larger area surrounding it (given the variability of the living data in the mathematical study model); utilizing real data derived from an alpine survey project as a model. Methods/Materials 10m2 and 30m2 quadrant samples from an alpine data base were obtained for examination.The data was limited to one species of plant surveyed in this model study. T-values were determined and compared for each of the L1 and L2 ranges of the large and smaller population samples for statistical validity at a 0.95 confidence level. Results The smaller population frequency was 0.24. At the 0.95 confidence level the interval was L1= .3815 and L2= .3815 for the larger population. The smaller population sample did not fit within the t-test confidence interval of the larger population. Conclusions/Discussion To support my conclusion I examined all nine quadrants of the larger 30m2 quadrant study area. No individual 10m2 quadrant fit the 0.95 confidence interval limits for the 30m2 quadrant population. This would clearly support my hypothesis.

Summary statement

Utilizing real research data I was able to confirm that using a small population sample does not accurately represent the larger population.

Help received

Thanks to Dr.Guy Norton and Dr.Dawn Hawkins of Cambridge University, England, for support and information, and research data from the GLORIA project.

Competition history

  • CSEF 2005 Mathematics & Software · Entry S1207

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