A popular misconception holds that the era of big data means the end of a need for sampling.
In fact, the proliferation of data of varying quality and relevance reinforces the need for sampling as a tool to work efficiently with a variety of data and to minimize bias.
Even in a big data project, predictive models are typically developed and piloted with samples.
Samples are also used in tests of various sorts (e.g., pricing, web treatments).
Figure 2-1 shows a schematic that underpins the concepts in this chapter.
The lefthand side represents a population that, in statistics, is assumed to follow an underlying but unknown distribution.
The only thing available is the sample data and its empirical distribution, shown on the righthand side.
To get from the lefthand side to the righthand side, a sampling procedure is used (represented by an arrow).
Traditional statistics focused very much on the lefthand side, using theory based on strong assumptions about the population.
Modern statistics has moved to the righthand side, where such assumptions are not needed.
Figure 2-1. Population versus sample
In general, data scientists need not worry about the theoretical nature of the lefthand side, and instead should focus on the sampling procedures and the data at hand. There are some notable exceptions. Sometimes data is generated from a physical ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month, and much more.
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
Julian F.
Head of Cybersecurity
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.
Addison B.
Field Engineer
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.
Amir M.
Data Platform Tech Lead
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
