While SAS and SPSS have many things in common, R is very different. My
goal in writing this book is to help you translate what you know about SAS or
SPSS into a working knowledge of R as quickly and easily as possible. I point
out how they differ using terminology with which you are familiar, and show
you which add-on packages will provide results most like those from SAS or
SPSS. I provide many example programs done in SAS, SPSS, and R so that
you can see how they compare topic by topic.
When finished, you should know how to:
Install R, choose a user interface, and choose and install add-on packages.
Read data from various sources such as text or Excel files, SAS or SPSS
data sets, or relational databases.
Manage your data through transformations, recodes, and combining data
sets from both the add-cases and add-variables approaches and restructuring
data from wide to long formats and vice versa.
Create publication-quality graphs including bar, histogram, pie, line, scatter,
regression, box, error bar, and interaction plots.
Perform the basic types of analyses to measure strength of association and
group differences, and be able to know where to turn to learn how to do
more complex methods.