My previous post made the point that it’s not a matter of whether it is good for you to use samples, but how good the sample you are using is. The comments on that post raised two different, and valid, perspectives about sampling. These viewpoints reflected two different use cases for data,
El Big Data y la Nube se están volviendo inseparables: “se necesitan recursos en la nube para el almacenamiento y la ejecución de proyectos de big data, y el big data brinda a las compañías una buena ocasión de pasar a la nube”. Podríamos decir que el big data y
In my previous post, I discussed sampling error (i.e., when a randomly chosen sample doesn’t reflect the underlying population, aka margin of error) and sampling bias (i.e., when the sample isn’t randomly chosen at all), both of which big data advocates often claim can, and should, be overcome by using all the data. In this
