In Chap. 2 we discussed the ideas of a population and a sample. Chapter 4 described probability distributions, which are used to model populations. Based on using the graphical tools discussed in Chap. 3 to look at your data, and based on your knowledge of the mechanism producing the data, you can model the data from your sampling program as having come from a particular kind of probability distribution. Once you decide on what probability distribution to use (if any), you usually need to estimate the parameters associated with that distribution. For example, you may need to compare the mean or 95th percentile of the concentration of a chemical in soil, groundwater, surface water, or air with some fixed standard. This chapter discusses the functions available in EnvStats for estimating distribution parameters and quantiles for various probability distributions, as well as constructing confidence intervals (CIs) for these quantities. See Millard et al. (2014) for a more in-depth discussion of this topic.
- Confidence Limit
- Lognormal Distribution
- Gamma Distribution
- Tolerance Interval
- Estimate Quantile
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Millard, S.P. (2013). Estimating Distribution Parameters and Quantiles. In: EnvStats. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8456-1_5
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