Intro R
Descriptive Statistics
• Descriptive statistics includes methods for organizing,
summarizing and visualizing data
Descriptive and Inferential Statistics
• Descriptive statistics includes methods for organizing,
summarizing and visualizing data
• Inferential statistics involves
(i) generalizing from a sample to the population from
which the sample was selected
(ii) assessing the reliability of such generalizations
But remember all the difficulties linguists have to
assemble a representative sample! This makes it rather
unsafe to generalize from a sample to the population.
We come back to this point when discussing tests.
23-04 Getting to know R: R syntax, data structures
30-04 Working with R: getting datasets, producing contingency tables, plots
07-05 Working with R: merging datasets, making maps
14-05 Working with R: hypothesis testing: Chi square and correlations
Roadmap for R classes
Formulate research question
Decide what and
how to measure
Collect data
Summarize data Analyze
data
Interpret results
Report results
Data representation & analysis Goals: produce different ways of representing data and testing hypotheses. Assignment (.2) at the end
What is R?
R is a language and environment for statistical
computing and graphics.
It’s an open source solution to data analysis
that’s supported by a large and active
worldwide research community.
Why use R?
• R is free!
• Just about any type of data analysis can be
done in R.
• R has state-of-the-art graphics capabilities.
Why use R?
• R can easily import data from a wide variety of
sources
• R runs on a wide array of platforms
• R has excellent on-line support
Disadvantages
• ease of use: work with a command line rather
than a graphical user interface (GUI),
i.e. typing instructions rather than pointing,
clicking, and dragging things with a mouse may
take a little getting used to.
Getting started
If you are using Windows, launch R from the
Start Menu. On a Mac, double-click the R icon
in the Applications folder.
Workspace PC with R console
Workspace Mac with R console
The editor window
• there are three windows that you use in R
– the console
– the graphics window (or quartz in MacOS)
– the editor window to write and save collections
of commands
The editor window
In the editor window, you can type all the commands, or scripts (series of commands) you want to be able to reproduce fast.
