TY - BOOK AU - Aslam, Muhammad  AU - Imdad Ullah, Muhammad TI - Practicing R for statistical computing SN - 9789819928880 U1 - 005.133 PY - 2023/// CY - Singapore PB - Springer KW - Statistical computing N1 - Table of content: Front Matter Pages i-xvii Download chapter PDF R Language: Introduction Muhammad Aslam, Muhammad Imdad Ullah Pages 1-6 Obtaining and Installing R Language Muhammad Aslam, Muhammad Imdad Ullah Pages 7-17 Using R as a Calculator Muhammad Aslam, Muhammad Imdad Ullah Pages 19-25 Data Mode and Data Structure Muhammad Aslam, Muhammad Imdad Ullah Pages 27-43 Working with Data Muhammad Aslam, Muhammad Imdad Ullah Pages 45-82 Descriptive Statistics Muhammad Aslam, Muhammad Imdad Ullah Pages 83-100 Probability and Probability Distributions Muhammad Aslam, Muhammad Imdad Ullah Pages 101-148 Confidence Intervals and Comparison Tests Muhammad Aslam, Muhammad Imdad Ullah Pages 149-172 Correlation and Regression Analysis Muhammad Aslam, Muhammad Imdad Ullah Pages 173-187 Graphing in R Muhammad Aslam, Muhammad Imdad Ullah Pages 189-223 Control Flow: Selection and Iteration Muhammad Aslam, Muhammad Imdad Ullah Pages 225-241 Functions and R Resources Muhammad Aslam, Muhammad Imdad Ullah Pages 243-250 Common Errors and Mistakes Muhammad Aslam, Muhammad Imdad Ullah Pages 251-261 Functions for Better Programming Muhammad Aslam, Muhammad Imdad Ullah Pages 263-272 Some Useful Functions Muhammad Aslam, Muhammad Imdad Ullah Pages 273-287 Important Packages Muhammad Aslam, Muhammad Imdad Ullah Pages 289-292 [https://link.springer.com/book/10.1007/978-981-99-2886-6) N2 - This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them. (https://link.springer.com/book/10.1007/978-981-99-2886-6) ER -