Close

Business Analytics with R

Other,

Updated On 02 Feb, 19

Overview

R Programming - Business Analytics with R - What is Data Mining ? - Data manipulation in R - Data visualization in R - What is R ? - Importing SPSS Data in R | SPSS Tutorial | Business Analytics with R - Introduction to SAS7BDAT | SAS7BDAT File Tutorial | SAS7BDAT Packages - Introduction to XML | Business Analytics with R | XML Tutorial | XML Tutorial for Beginners - Introduction To Exploratory Data Analysis | Business Analytics with R - Statistical Modeling in Business Analytics with R - Modeling Techniques in Business Analytics with R - Predictive Analytics Process | Business Analytics with R - Cluster Analysis Steps In Business Analytics with R - Who Uses R ? - What is Business Analytics? - Analysis Of Variance in R - Association Rule Mining in R - Understanding Linear Regression in R - Understanding Logistic Regression in R - Introduction to Business Analytics with R - R Programming Language - Installation of R Package - Understanding R Console - Statistical Modeling in Business Analytics with R - Machine Learning with R - Understanding Decision tree in Business Analytics with R - Understanding the Concept of Statistics Essentials for Analytics - Introduction to Data Import - Business Analytics with R | Stages of Analytics | Data Mining | What is R

Includes

On-demand Videos
Login & Track your progress
Full Lifetime acesses

Lecture 10: Introduction To Exploratory Data Analysis | Business Analytics with R

4.1 ( 11 )

Lecture Details

Watch Sample Class Recording
httpwww.edureka.cor-for-analytics?utm_source=youtube&utm_medium=referral&utm_campaign=exploratory-data-analysis

Exploratory Data Analysis is an approach of analyzing data sets to summarize their main characteristics, often with visual methods. Promoted by John Tukey for encouraging statisticians to explore the data, EDA helps in identifying the outliers, trends, and patterns. Watch the video to learn about the following topics related to EDA
1. Exploratory Data Analysis
2. Data Manipulation in R
3. Data Exploration in R
4. Boxplots and Histograms
5. Slicing and Dicing of data
6. Data Transformation and Aggregation for Analysis
7. Packages in R for Data Analysis
8. Common Analytical Mistakes

Related Blogs
httpwww.edureka.coblogwhy-should-a-statistical-professional-know-r?utm_source=youtube&utm_medium=referral&utm_campaign=EDA
httpwww.edureka.coblogwhy-learn-r?utm_source=youtube&utm_medium=referral&utm_campaign=EDA
httpwww.edureka.coblogimportingspss-data-r?utm_source=youtube&utm_medium=referral&utm_campaign=EDA
Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world.
The topics related to ‘Exploratory Data Analysis’ have extensively been covered in our course ‘Business Analytics with R’.
For more information, please write back to us at sales@edureka.co
Call us at US 1800 275 9730 (toll free) or India +91-8880862004