Book Image

R Data Science Essentials

Book Image

R Data Science Essentials

Overview of this book

With organizations increasingly embedding data science across their enterprise and with management becoming more data-driven it is an urgent requirement for analysts and managers to understand the key concept of data science. The data science concepts discussed in this book will help you make key decisions and solve the complex problems you will inevitably face in this new world. R Data Science Essentials will introduce you to various important concepts in the field of data science using R. We start by reading data from multiple sources, then move on to processing the data, extracting hidden patterns, building predictive and forecasting models, building a recommendation engine, and communicating to the user through stunning visualizations and dashboards. By the end of this book, you will have an understanding of some very important techniques in data science, be able to implement them using R, understand and interpret the outcomes, and know how they helps businesses make a decision.
Table of Contents (15 chapters)
R Data Science Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we covered how to implement various exploratory data analysis techniques using the Titanic dataset. Additionally, you learned descriptive statistics to summarize the dataset quantitatively as simple quantitative statements or as a visual representation using the summary function as well as the box plots. Moreover, we covered inferential statistics to infer the properties of the dataset that are of interest. Further, you also learned about univariate analysis, where the analysis is done using only one variable at a time to understand the data, and bivariate analysis, where the analysis is done using two variables to understand the data. The effect of one variable over the other was also covered. Finally, we explored multivariate analysis by considering more than two variables for the study by performing single variable analysis and then, double variable analysis, and finally, we considered the significant one for multivariate analysis using the scatter plot with segments...