Precision and Error

Precision of a sample can be described as the variation among all the samples used to estimate the population parameters. In this respect it is analogous to the sample variance, and is reflected in the width of the confidence interval of a sample. Precision is affected by various compensating 'errors' associated with inherent variability of the population, as well as random measurement errors, such as possible inconsistent assessments when making estimates, for example, the designation of classes in the Daubenmire cover class method to determine cover, or the designation of ranks in the comparative yield method to determine biomass.

Precision is an important factor to consider when designing the inventory or monitoring program because the sample variance is the foundation of subsequent statistical analysis. Therefore, although sampling precision can be quantified from the collected data, it is used as an expression of the confidence we have in our collected data. Highly variable samples have a low precision, meaning we are unsure how well our particular sample represents the population.

The best way to ensure precise data is to incorporate safeguards into the sampling process that protect against errors. These safeguards include:

References and Further Reading

Bonham, C.D. 1989. Measurements for terrestrial vegetation. John Wiley Son, New York, NY. pp 10-11.

Cook, C.W., and J. Stubbendieck. (eds). 1986. Range research: Basic problems and techniques. Society for Range Management, Denver, CO. pp 215-220.

Greig-Smith, P. 1983. Quantitative plant ecology. Blackwell Scientific Publications, Oxford.3rd ed. pp 25-26.