We are continuing to explore ggplot in Part II of our textbook,
Visualize. This week we're going to practice using our plots to explore
data sets, generating and answering basic questions about our data. This is called
Exploratory Data Analysis.
This chapter is different from the previous chapters in that you focus on
thinking about what you might see in the data, instead of learning a new
collection of functions and arguments. The authors shift the focus from the
tools to the data.
As you gain experience, looking for patterns in data will depend on your comfort
and familiarity with statistics. Data science involves practical applications of
statistics.
This textbook is accessible in that it does not demand that you are experienced
in statistics, but the result of that choice is that the authors dig quickly and
deeply into the tools and the programming concepts.
For that reason the authors gently introduce the three broad statistical concepts
that you keep in mind when you examine any data.
variation
describing how values of a single variable differ from each other
covariation
describing how values of a two variable may relate to each other
models
recognizing and describing the relationships between variables.
Assessment deadlines will be 11:59pm each Saturday.
All assessments are submitted to the Homework Folder inside your assigned
Google Drive folder.
There are no make-ups for missed assessments. Contact me before a deadline
if you have an issue meeting the deadline and we will find a mutually
agreeable solution.
Homework
Homework 6 (due Saturday, February 15)
The instructions for your homework are contained in the R script
file
homework_06.R.