Statistical Application Development with R and Python

Software Implementation Illustrated with R and Python

Key Features

• Learn the nature of data through software which takes the preliminary concepts right away using R and Python.
• Understand data modeling and visualization to perform efficient statistical analysis with this guide.
• Get well versed with techniques such as regression, clustering, classification, support vector machines and much more to learn the fundamentals of modern statistics.

Book Description

What you will learn

• Learn the nature of data through software with preliminary concepts right away in R
• Read data from various sources and export the R output to other software
• Perform effective data visualization with the nature of variables and rich alternative options
• Do exploratory data analysis for useful first sight understanding building up to the right attitude towards effective inference
• Learn statistical inference through simulation combining the classical inference and modern computational power
• Delve deep into regression models such as linear and logistic for continuous and discrete regressands for forming the fundamentals of modern statistics
• Introduce yourself to CART – a machine learning tool which is very useful when the data has an intrinsic nonlinearity

Who this book is for

If you want to have a brief understanding of the nature of data and perform advanced statistical analysis using both R and Python, then this book is what you need. No prior knowledge is required. Aspiring data scientist, R users trying to learn Python and vice versa