What is Exploratory Data Analysis(EDA)?

In statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.

Based on the results of EDA, companies also make business decisions, which can have repercussions later.

• If EDA is not done properly then it can hamper the further steps in the machine learning model building process.
• If done well, it may improve the efficacy of everything we do next.

Introduction to Univariate, Bivariate and Multivariate Analysis

In the field of data, there is nothing more important than understanding the data that you are trying to analyze. In order to understand the data is it important to understand the purpose of the analysis because this will help you save time and dictate how to go about analyzing the data.

There are a lots of different tools, techniques and methods that can be used to conduct your analysis. You could use software libraries, visualization tools and statistic testing methods.

Regardless if you are a Data Analyst or a Data Scientist, it is crucial to know Univariate, Bivariate and Multivariate statistical analysis.