ASCOT Library Zabali Campus

Includes bibliographical references and index.

1. Data, Stats and Stories - An Introduction 1 -- 2.Python Programming Primer 33 -- 3.Snakes, Bears & Other Numerical Beats: NumPy, SciPy & pandas 99 -- 4. The Measure of All Things - Statistics 141 -- 5.Definitely Maybe: Probability and Distribution 179 -- 6.Alluring Arguments and Ugly Facts - Statistical Modelling and Hypothesis Testing 267 -- 7.Delightful Details - Data Visualisation 383 -- 8.Dazzling Data Design - Creating Charts 417 -- A. Variance : Population v Sample 477 -- B Sum of First n Integers 479 -- C. Sum of Square of the First n Integers 481 -- D. The Binomial Coefficient 483 -- E. The Hypergeometric Distribution 485 -- F. The Poisson Distribution 487 -- G. The Normal Distribution 491 -- H.Skewness and kurtosis 495 -- I. Kruskal-Wallis Test - No Ties 497.

"This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers that have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics, and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications"-- Provided by publisher.