Data analysis has been a hot topic for a number of years, and many
future data scientists have backgrounds that are relatively light
in mathematics. This slim volume provides a very approachable guide
to the techniques of the subject, designed with such people in
mind. Formulae are kept to a minimum, but the book's scope is
broad, introducing the basic ideas of probability and statistics
and more advanced techniques such as generalised linear models,
classification using logistic regression, and support-vector
machines. An essential feature of the book is that it does not tie
to any particular software. The methods introduced in this book
could also be implemented using any other statistical software and
applying any major statistical package. Academically, the book
amounts to a first course, practical for those at the undergraduate
level, either as part of a mathematics/statistics degree or as a
data-oriented option for a non-mathematics degree. The book appeals
to would-be data scientists who may be formula shy. However, it
could also be a relevant purchase for statisticians and
mathematicians, for whom data science is a new departure, overall
appealing to any computer-literate reader with data to analyse.
General
Imprint: |
Oxford UniversityPress
|
Country of origin: |
United Kingdom |
Release date: |
August 2023 |
Authors: |
Graham Upton
• Dan Brawn
|
Dimensions: |
234 x 156mm (L x W) |
Pages: |
160 |
ISBN-13: |
978-0-19-288577-7 |
Categories: |
Books
|
LSN: |
0-19-288577-4 |
Barcode: |
9780192885777 |
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