Exploring Your First Data Set with R

Focused View

Martin Burger

2:05:02

20 View

01 - Course Overview

01 - Course Overview.mp4

01:47

02 - Background on Exploratory Data Analysis

02 - Intro.mp4

01:38

03 - Managing Expectations.mp4

04:51

04 - The Data Science Steps.mp4

06:32

05 - Blueprint to Data Exploration.mp4

04:39

06 - R for Data Exploration.mp4

04:45

07 - Our Course Dataset.mp4

03:04

08 - Summary.mp4

01:38

03 - First Level Data Exploration

09 - Intro.mp4

02:28

10 - Summary Statistics.mp4

07:44

11 - Boxplots and Data Structure.mp4

07:48

12 - Probability Distributions.mp4

05:41

13 - Testing the Distribution.mp4

05:23

14 - Hypothesis Tests.mp4

07:41

15 - Summary.mp4

02:48

04 - Statistical Tests to Confirm Initial Findings

16 - Intro.mp4

01:54

17 - Relationships Between Variables- Overview.mp4

03:47

18 - Relations between Categorical and Numeric Variables.mp4

07:42

19 - Relations in Numeric Variables.mp4

05:43

20 - Visualizing Numeric Correlations.mp4

04:04

21 - Relations between Categorical Variables.mp4

05:55

22 - Comparing the Methods Used.mp4

05:53

23 - Summary.mp4

01:53

05 - Looking Ahead and Summary

24 - Intro.mp4

01:08

25 - The Steps after Exploration.mp4

03:40

26 - Alternative Datasets and Data Exploration.mp4

05:01

27 - Optimizing Your R Learning Experience.mp4

05:36

28 - Course Summary.mp4

04:19

Description

Learn how to explore new data sets in R by applying a structured and established data exploration blueprint.

What You'll Learn?

Do you want to learn how data exploration can be implemented in R? Without data exploration, the whole data analysis process gets inefficient and slow, but follow a good data exploration process and you'll be guided to valuable insights. In this course, Exploring Your First Data Set with R, you will learn how new datasets are explored and analyzed in a quick and efficient way. First, you will learn the methods outlined, following a logical succession, which are applicable in most standard data frames. Then, you will discover how the process is divided into 3 steps: summary statistics, distribution checks, and relation analysis. These steps build on each other and you will find out which variables are worth further analysis and where variable dependencies exist. Finally, you will gain the knowledge of the ground work for machine learning and final data presentation.

When you’re finished with this course, you’ll have the skills to properly structure and conduct data exploration in R.

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R Programming

Martin Burger

Instructor's Courses

Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.