Statistics Review - Mathematics and Statistics for the Environment - page 107

7 Statistics Review
There are three kinds of lies: lies, damned lies, and statistics.
—Benjamin Disraeli
To the uninitiated it may often appear that the statistician's primary function is to prevent or at least
impede the progress of research. And even those who suspect that statistical methods may be more
boon than bane are at times frustrated in their efforts to make use of the statistician's wares.
—Frank Freese (1967)
7.1 STATISTICAL CONCEPTS *
Despite the protestation of Disraeli and the wisdom of Freese, environmental practice includes the
study of and use of statistical analysis of the results. The principal concept of statistics is that of
variation. Variation is often found when conducting typical environmental health functions requir-
ing the use of biostatistics , where a wide range of statistics are applied to an even wider range of
topics in biology, such as toxicological or biological sampling protocols for air contamination, and
other environmental functions applied to agriculture, forestry, fisheries, and other specialized areas.
This chapter provides environmental practitioners with a survey of the basic statistical and data
analysis techniques that can be used to address many of the problems that they will encounter on
a daily basis. It covers the data analysis process, from research design to data collection, analysis,
reaching conclusions, and, most importantly, the presentation of findings.
Finally, it is important to point out that statistics can be used to justify the implementation of a
program, identify areas that need to be addressed, or evaluate the impact that various environmental
health and safety programs might have on losses and accidents. A set of occupational health and
safety 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. For example, the importance of using statistical data
when selling an environmental health and safety plan or some other type of environmental opera-
tion and trying to win over those who control the purse strings cannot be overemphasized.
With regard to Freese's opening statement, much of the difficulty is due to not understanding the
basic objectives of statistical methods. We can boil these objectives down to two:
1. Estimation of population parameters (values that characterize a particular population)
2. Testing hypotheses about these parameters
A common example of the first is estimation of the coefficients a and b in the linear relationship
Y = a + bX . To accomplish this objective one must first define the population involved and specify
the parameters to be estimated. This is primarily the research worker's job. The statistician helps
devise efficient methods of collecting the data and calculating the desired estimates.
* Much of the information in this chapter is modeled after Freese, F., Elementary Statistical Methods for Foresters ,
Handbook 317, U.S. Department of Agriculture, Washington, DC, 1967.
109