Statistical Data Analysis Using R A Practical Introduction

This book introduces statistical data analysis using R programming, covering tools like descriptive statistics, regression, ANOVA, and non-parametric tests. It covers essential statistical tools, including descriptive statistics, probability distributions, and hypothesis testing, with practical examples and solved exercises. It introduces both built-in library packages and manual coding solutions, offering flexibility and clarity for learners. Featuring numerous tables, diagrams, and hands-on programming exercises, this book ensures ease of understanding and practical mastery of R for statistical analysis. Comprehensive coverage of statistical tools, including descriptive statistics, regression, ANOVA, and non-parametric tests. Includes dual programming approach, in-built library packages and manual coding solutions. Focus on graphics and data visualisation for effective interpretation of results. Practical R code examples and solved exercises for hands-on learning. This book is for undergraduate and postgraduate students, researchers, and professionals in fields such as statistics, computer science, business analytics, public health, psychology, economics, and environmental science.