Exploratory Data Analysis (EDA) with R
Learn to analyze data distributions, explore variable relationships, and identify data quality issues using R. This course will help you interpret distributions and improve decision-making through effective data analysis.
What you'll learn
Business decisions often fail due to poor understanding of data patterns, relationships, and quality issues in the analysis phase.
In this course, Exploratory Data Analysis (EDA) with R, you'll gain the ability to thoroughly analyze data for better decision-making.
First, you'll explore how to summarize and interpret data distributions using descriptive statistics.
Next, you'll discover patterns and relationships between variables through correlation analysis and grouped summaries.
Finally, you'll learn how to identify and assess data quality issues including missing values, outliers, and inconsistencies.
When you're finished with this course, you'll have the skills and knowledge of statistical analysis needed to perform comprehensive exploratory data analysis and ensure reliable insights for decision-making.
Table of contents
About the author
Hello, I'm Ali. I have a PhD in computer science. I am currently conducting research on natural language processing (NLP) using Python and machine learning. I have a YouTube channel, named Flutterware, that shares tutorial on Google's Flutter platform that is used to develop mobile applications for Android and iOS with one base code. I love research and exploring knowledge. I think acquiring knowledge without sharing it is useless. I hope that you find my classes helpful.