June 2016
Beginner to intermediate
284 pages
6h 22m
English
Content preview from Mastering Python Data AnalysisBecome 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,
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Chapter 3. Learning About Models
In the most generic sense, a model is an approximate description of a portion of reality. Models are essential to science and, in fact, any area of knowledge: it is only possible to comprehend the world by concentrating on a small part of it at a time and making suitable simplifications.
In this chapter, we will discuss the following topics:
- Using basic models in data analysis
- Using the cumulative distribution function and probability density function to characterize a variable
- Using the preceding functions and various tools to make point estimates and generating random numbers with a certain distribution
- Discussing examples of discrete and continuous random variables and an overview of multivariate distributions
Models ...
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