October 2014
Beginner to intermediate
348 pages
6h 55m
English
Content preview from 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. Statistics and Linear Algebra
Statistics and linear algebra are branches of mathematics that are especially useful for data analysis. That's why we will focus on them in this chapter. Statistics is needed to make inferences from raw data. For instance, we can compute that the data for a variable has a certain arithmetic mean and standard deviation. From these numbers, we can then infer a range and the expected value for this variable. Then, we can run statistical tests to check how likely it is that we made the right conclusion.
Linear algebra concerns itself with systems of linear equations. These are easy to solve with NumPy and SciPy using the linalg package. Linear algebra is useful, for instance, to fit data to a model. We shall ...
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