Free Course
Data Analysis with R
by
Visually Analyze and Summarize Data Sets
About this Course
Exploratory data analysis is an approach for summarizing and visualizing the important characteristics of a data set. Promoted by John Tukey, exploratory data analysis focuses on exploring data to understand the data’s underlying structure and variables, to develop intuition about the data set, to consider how that data set came into existence, and to decide how it can be investigated with more formal statistical methods.
If you're interested in supplemental reading material for the course check out the Exploratory Data Analysis book. (Not Required)
This course is also a part of our Data Analyst Nanodegree.
Course Cost
Free
Timeline
Approx. 2 months
Skill Level
intermediate
Included in Product
Rich Learning Content
Interactive Quizzes
Taught by Industry Pros
Self-Paced Learning
Course Leads
Moira Burke
Instructor
Chris Saden
Instructor
Solomon Messing
Instructor
Dean Eckles
Instructor
What You Will Learn
Prerequisites and Requirements
A background in statistics is helpful but not required. Consider taking Intro to Descriptive Statistics prior to taking this course. Relevant topics include:
- Mean, median, mode
- Normal, uniform, and skewed distributions
- Histograms and box plots
Familiarity with the following CS and Math topics will help students:
- Variable assignment
- Comparison and logical operators ( <, >, <=, >=, ==, &, | )
- If else statements
- Square roots, logarithms, and exponentials
See the Technology Requirements for using Udacity.
Why Take This Course
You will...
- Understand data analysis via EDA as a journey and a way to explore data
- Explore data at multiple levels using appropriate visualizations
- Acquire statistical knowledge for summarizing data
- Demonstrate curiosity and skepticism when performing data analysis
- Develop intuition around a data set and understand how the data was generated.
What do I get?
- Instructor videos
- Learn by doing exercises
- Taught by industry professionals