This book introduces you to the world of data science. It
reveals the proper way to do data science. It covers essential
statistical and programming techniques to help you understand
data science from a broad perspective. Not only that, but it
provides a theoretical, technical, and mathematical foundation for
problem-solving using data science techniques.
This chapter covers the parametric method , also called the
linear method . Understanding how to test a regressor under
the violation of regression assumptions will enable you to tackle
problems in subsequent chapters with ease. While reading, it is
important to remember that the example data has one
dependent variable. This chapter does not cover multicollinearity
with a variance inflation factor (VIF).
Practical R 4: Applying R to Data Manipulation, Processing and Integration
Get started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio. Utilizing many examples and projects, this book teaches you how to get data into R and how to work with that data using R. Once grounded in the fundamentals, the rest of Practical R...
Authentication and Access Control: Practical Cryptography Methods and Tools
The advent of the Internet has allowed for many services and applications, most
notably in communications between users, servers, and devices. Unfortunately,
this has led to many security challenges and problems. Recent examples include
password leakage on large social network sites and defacement of websites. It is,