
06643747
j
2016f.01304
Johnson, Roger W.
Kliche, Donna V.
Smith, Paul L.
Modeling raindrop size.
J. Stat. Educ. 23, No. 1, 26 p., electronic only (2015).
2015
Taylor \& Francis, Abingdon, Oxfordshire; American Statistical Association (ASA), Alexandria, VA
EN
K90
K70
K40
M50
stochastics
statistics
teaching
exploratory data analysis
data sets
distribution
parameter estimation
maximum likelihood estimation
disdrometer
beta density
exponential density
gamma density
lognormal density
Weibull density
applied statistics
parametric models
quality of fit
mathematical applications
meteorology
http://ww2.amstat.org/publications/jse/v23n1/johnson.pdf
Summary: Being able to characterize the size of raindrops is useful in a number of fields including meteorology, hydrology, agriculture and telecommunications. Associated with this article are data sets containing surface (i.e. groundlevel) measurements of raindrop size from two different instruments and two different geographical locations. Students may begin to develop some sense of the character of raindrop size distributions through some basic exploratory data analysis of these data sets. Teachers of mathematical statistics students will find an example useful for discussing the beta, gamma, lognormal and Weibull probability density models, as well as fitting these by maximum likelihood and assessing the quality of fit. R software is provided by the authors to assist students in these investigations.