Atsiliepimai
Aprašymas
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.
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.
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.
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.
Atsiliepimai