Concentration ratios (CR(wo-media)) are used in most radioecological models to predict whole-body radionuclide activity concentrations in wildlife from those in environmental media. This simplistic approach amalgamates the various factors influencing transfer within a single generic value and, as a result, comparisons of model predictions with site-specific measurements can vary by orders of ma...

SUMMARY The log-transformation is widely used in biomedical and psychosocial research to deal with skewed data. This paper highlights serious problems in this classic approach for dealing with skewed data. Despite the common belief that the log transformation can decrease the variability of data and make data conform more closely to the normal distribution, this is usually not the case. Moreove...

We describe bivariate cartograms, a technique specifically designed to allow for the simultaneous comparison of two geo-statistical variables. Traditional cartograms are designed to show only a single statistical variable, but in practice, it is often useful to show two variables (e.g., the total sales for two competing companies) simultaneously. We illustrate bivariate cartograms using Dorling...

Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distrib...

This short note explains in simple terms why the normal distribution is so ubiquitous in pattern recognition applications. As we will see, the answer comes from information theory: when we compress a data set by keeping only the mean and variance of the problem’s classes, the distribution which allows us to keep on working probabilistically, while making minimal assumptions about the data, is, ...

Let U and V be two independent normal random variables, and consider two new random variables X and Y of the form X = aU + bV, Y = cU + dV, where a, b, c, d, are some scalars. Each one of the random variables X and Y is normal, since it is a linear function of independent normal random variables.† Furthermore, because X and Y are linear functions of the same two independent normal random variab...

In this article we introduce a new three parameter skewed distribution of which normal distribution is a special case. This distribution is obtained by using geometric sum of independent identically distributed normal random variables. We call this distribution as the geometric skew normal distribution. Different properties of this new distribution have been investigated. The probability densit...

let x be a random variable from a normal distribution with unknown mean θ and known variance σ2. in many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. as the usual estimator of θ, i.e., x under the linex loss function is inadmissible, finding some competitors for x becomes worthwhile. the only study in the literature considered the problem of min...

In this paper, we introduce a new skewed distribution of which normal and power normal distributions are two special cases. This distribution is obtained by taking geometric maximum of independent identically distributed power normal random variables. We call this distribution as the power normal--geometric distribution. Some mathematical properties of the new distribution are presented. Maximu...