Description
Course info
Rating
(314)
Level
Beginner
Updated
Nov 13, 2015
Duration
2h 30m
Description

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for exploratory data analysis. This course will provide an introduction to the R programming language and demonstrate how R can be used for exploratory data analysis to complete day-to-day developer tasks.

About the author
About the author

Matthew is a data science consultant, author, and international public speaker. He has over 17 years of professional experience working with tech startups to Fortune 500 companies. He is a Microsoft MVP, ASPInsider, and open-source software contributor.

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Section Introduction Transcripts
Section Introduction Transcripts

Transforming and Cleaning Data
Welcome back to Exploratory Data Analysis with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to transform and clean our data to prepare it for exploratory data analysis. First we'll begin with an introduction to data munging or the process of transforming and cleaning our data. Next we'll learn how to load data into R. Then we'll learn how to clean and transform our data. Next we'll learn how to export data into various formats. Finally, we'll see a demo where we'll put all these steps together.

Calculating Descriptive Statistics
Hello again and welcome back to Exploratory Data Analysis with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to calculate descriptive statistics for our data. First we'll begin with an introduction to descriptive statistics, that is describing the characteristics of our data in meaningful ways. Next we'll learn about the types of analysis that we can perform on our data. Then we'll learn how to avoid making errors and invalid claims with our descriptive statistics. Finally, we'll see a demo where we'll put all these concepts together.

Visualizing Data
Welcome back to Exploratory Data Analysis with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to visualize our data with the basic plotting system in R. First we'll begin with an introduction to data visualization, that is representing the characteristics of our data in visual ways. Next, we'll learn about the types of data visualizations that we can create for our data. Then we'll learn how to create clean data visualizations and avoid making mistakes with our visualizations. Finally, we'll see a demo where we'll put all these concepts together.

Moving Beyond R and Exploratory Data Analysis
Hello and welcome back to this final module in Exploratory Data Analysis with R. I'm Matthew Renze with Pluralsight and in this module we'll look at a few topics that move beyond R and exploratory data analysis. First, we'll start with other types of data analysis we can perform beyond exploratory data analysis. Next, we'll see a demo of two additional types of analysis we can perform, that is linear regression analysis and cluster analysis. Then we'll learn about alternatives to R for performing exploratory data analysis. Finally, we'll wrap things up by concluding the module and the course as a whole.