Estimation of Time to Excessive Microbial Count

model

lognormal

normal

log-Laplace

Laplace

model parameters

μ

lN

5.

σ

lN

5.

threshold

10000

run to plot

1

run length n

100

number of runs

500

seed repeatable random numbers

seed value

0

generate new data runs

Many microbial count records in foods and water resemble a random time series. The distribution of the entries allows you to estimate the frequency of future counts exceeding a level deemed undesirable or dangerous. This Demonstration lets you generate Monte Carlo simulations of such counts using the lognormal, normal, log-Laplace, or Laplace distribution function as a model, with hypothetical or experimentally determined parameters, and record the times at which a specified threshold has been exceeded. You can use the distribution and histogram of these times to assess how soon an excessive count might be encountered if conditions remain unchanged.