Data Analysis with R

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Data Analysis with R

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About the course

Data Analysis with R

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 Leads
Moira Burke

Moira Burke

Instructor

Chris Saden

Chris Saden

Instructor

Solomon Messing

Solomon Messing

Instructor

Dean Eckles

Dean Eckles

Instructor

Course Cost
Free
Timeline
Approx. 2 months
Skill Level
intermediate
Pre-Requisites & 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

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