Non-Parametric Statistical Analysis with R

Non-Parametric Statistical Analysis with R

Explore with the Power of R

This book is a learning and reference resource that explains non-parametric statistical analysis methods with examples and applications. The book has been written with an approach that makes it easier for researchers to choose and apply methods suitable for their purpose. In this book, non-parametric statistical analyzes are made with R. R is the most popular analysis and software environment for statistical computing and graphics processing. R, which is a free software that can meet almost every need in data science with around sixteen thousand packages, is also very powerful in terms of non-parametric statistical methods. R is also a programming language and provides great convenience to data scientists and researchers who want to develop their own statistical applications and test their theories. The book also provides examples of such programming in relation to non-parametric statistical methods.

INGREDIENTS

Installing R

Data Types and Operations in R

Reading and Writing Files in R

Parametric Assumptions and Control

Single Sample Tests

Two Sample Tests

Non-Parametric Tests on One-Way Classified Data

Sequence Assignment Operations

Non-Parametric Tests on Bidirectional Classified Data

Post-Tests: Post-hoc Analysis

Analysis of Factorial Trials

Correlation and Regression Analysis

Randomness Analysis

Analysis of Categorical Data