Data Analysis: A Gentle Introduction for Future Data Scientists

Data analysis has been a hot topic for years, and this book provides an approachable guide to the techniques, designed with non-mathematics backgrounds in mind. It covers basic ideas of probability and statistics, as well as advanced techniques such as generalised linear models, classification using logistic regression, and support-vector machines. It does not tie to any particular software and is suitable for undergraduates and data-oriented readers.

Format: Paperback / softback
Length: 160 pages
Publication date: 28 August 2023
Publisher: Oxford University Press

For several years, data analysis has been a popular subject, and many aspiring data scientists lack a strong mathematical background. This slender volume offers a user-friendly introduction to the subject's techniques, with a focus on individuals with limited mathematical expertise. While formulae are kept to a minimum, the book covers a wide range of topics, including probability and statistics, as well as advanced techniques such as generalised linear models, logistic regression classification, and support-vector machines. One of the book's key strengths is its independence from any specific software. The methods presented herein can be implemented using various statistical software packages and any major statistical package. From an academic perspective, the book serves as a comprehensive first course, suitable for undergraduates pursuing a mathematics or statistics degree or as a data-oriented option for non-mathematics majors. It appeals to aspiring data scientists who may feel hesitant about formulas but also holds value for statisticians and mathematicians transitioning into data science. The book's content is accessible to computer-literate readers with data to analyse, making it a valuable resource for anyone interested in leveraging data for insights and decision-making.

Weight: 280g
Dimension: 156 x 235 x 13 (mm)
ISBN-13: 9780192885784