ABSTRACT
Despite Disraeli’s protestation, forest-based biomass energy production leans heavily on statistical applications. The principal concept of statistics is that of variation. When conducting typical forest-based biomass monitoring, sampling, and processing, variation is commonly found. Variation comes from the methods that were employed in the sampling process or, in this example, in the distribution of forest-based biomass. Several complex statistical tests can be used to determine the accuracy of data results; however, it is impossible to treat all aspects of statistics in one chapter. Instead, the aim of this chapter is simply to provide an overview of statistical concepts utilized in forest-based biomass and data analysis. Moreover, the intent is to provide a brief summary of and calculation procedures for the basic, fundamental statistical parameters. Specifically, this chapter provides a survey of the basic statistical and data analysis techniques that can be applied to solving many problems encountered on a daily basis. It covers the data analysis process: research design, data collection, analysis, drawing conclusions, and, most importantly, presentation of findings. Finally, it is important to point out that statistics can be used to justify the implementation of a program or process, identify areas that need to be addressed, or illustrate the impact that various environmental parameters, such as lightning-sparked forest fires, insect infestation, and so forth, have on losses and accidents. A set of forest data (or other data) is only useful if it is analyzed properly. Better decisions can be made when the nature of the data is properly characterized-that is, when precision, accuracy, and bias are considered.
