Data Analysis with R
R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples.
Offered by
Difficulty Level
Intermediate
Completion Time
19h
Language
English
About Book
Who Is This Book For?
Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book.
Data Analysis with R
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 19h total length
RefresheR
The Shape of Data
Describing Relationships
Probability
Using Data to Reason about the World
Testing Hypotheses
Bayesian Methods
The Bootstrap
Predicting Continuous Variables
Predicting Categorical Variables
Predicting Changes with Time
Sources Of Data
Dealing with Missing Data
Dealing with Messy Data
Dealing with Large Data
Working with Popular R Packages
Reproducibility and Best Practices
Related Resources
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