Statistical Tools for the Comprehensive Practice of Industrial Hygiene and Environmental Health Sciences
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About the Book
This book reviews and reinforces concepts and techniques typical of a first statistics course with additional techniques useful to the IH/EHS practitioner.
The occupational health, safety, and environmental science fields are data intensive. Industrial hygiene and environmental health sciences (IH/EHS) professionals spend a lot of their time measuring things, and do so with the goal of answering a specific question. How they go about the measurements – the what, when, where, who, and how of the measurements – is driven by the why. That is, by the question they are trying to answer. However, the data always has some uncertainty because of measurement variability, and statistics helps the user see through the fog of uncertainty in order to draw accurate inferences about what is being measured. Most undergraduate and graduate programs in industrial hygiene and environmental health sciences recognize the value of statistical tools, and require an introductory statistics course. Additional statistical tools and techniques – beyond those usually covered in a basic course – are typically needed. Statistical Tools for the Comprehensive Practice of Industrial Hygiene and Environmental Health Sciences reviews and reinforces the concepts and techniques typical of a first statistics course, and supplements them with additional graphical and nonparametric techniques that may be particularly useful to the IH/EHS practitioner.
Organized into thirteen chapters Statistical Tools for the Comprehensive Practice of Industrial Hygiene and Environmental Health Sciences features techniques for:
Students in industrial hygiene, safety, safety engineering, environmental engineering, environmental health, environmental sciences, and similar programs, and graduates of these programs who are already practicing professionals will benefit from the techniques covered in this text. Analysis using the readily available Excel® statistical functions is emphasized, so that special statistical software and programming expertise are not required.
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