With statistical sampling, counsel can simplify damage analyses, avoid potential issues with incomplete or missing data, and minimize the risk of error. In our prior ...

In a unanimous decision, the California Supreme Court on May 29 reversed a class action verdict for a class which was based on a flawed statistical model to determine liability and damages. Duran v. U ...

Sampling is the process of collecting some data when collecting it all or analyzing it all is unreasonable. Before addressing why sampling still matters when massive amounts of data are available and ...

Sampling populations, calculating weighted estimates, and accounting for errors, outliers, and uncertainty are important steps in our work to produce recreational catch statistics. There are two broad ...

This paper proposes a novel logarithmic-type estimator for the estimation of the population mean under stratified random sampling when a single auxiliary variable is available. By employing a ...

Statistical estimation in survey sampling encompasses a range of methods designed to infer population parameters from observed data in a manner that is both unbiased and efficient. Traditional ...