Quantitative Methods In Linguistics (9781405144254): Keith Johnson. Analyzing Linguistic Data: A Practical Introduction to Statistics using R (9780521709187): R. H. Baayen. Statistics in Language Studies (Cambridge Textbooks in Linguistics) (9780521273121): Anthony Woods, Paul Fletcher, Arthur Hughes. Statistics for Linguistics with R: A Practical Introduction (Mouton Textbook) (9783110205657): Stefan Th. Gries. The R Project for Statistical Computing.
Software Resources for R. Software Resources for R Below is a list of resource pages for using R to do statistics.
On each page a set of data are explored with the software. Some commentary is given on interpretation but the main focus is on getting the software to do the work. What the numbers mean should come from your prior statistical training or the statistics.com course you are currently taking. Each page listed below has a title you can click on to read the page. Getting Started Entering data Simple summary statistics Stem and leaf plots Histograms Boxplots Dotplots Logarithmic transformations Saving your data Summarizing Quantitative Data Simple summary statistics Boxplots comparing two groups Transformations Summarizing a Single Categorical Variable Mode Tables Bar charts Pie charts Making and Interpreting Tables for Two Categorical Variables One- and Two-Way Tables Probability and two-way tables Inference for One Proportion Confidence interval Hypothesis test Inference for Two Proportions.
Introduction to R. Learning R. Start [R Wiki] * R is a free software environment for statistical computing and graphics. It runs on a wide variety of UNIX platforms, Windows and MacOS. This R Wiki is dedicated to the collaborative writing of R documentation. For information on browsers, RSS syndication, copyright, ... read usage. R comes with several official manuals and FAQs. These should be your primary source of information. Personal note: I have some difficulties with the statement that the official manuals should be your primary source of information. Books I found ordinary books to be the most helpful source of information for novice programmers and I can particularly recommend: Adler, J. (2010) R in a nutshell. Help forum for programmers The R-Help mailing list can give excellent answers, but due to the high calibre of respondents it can be intimidating, (and off-putting).
In addition I can’t but feel that many questions are a waste of time for most of those who respond. Stackoverflow Table of contents (click on an item to expand) R by example. Basics Reading files Graphs Probability and statistics Regression Time-series analysis All these examples in one tarfile.
Outright non-working code is unlikely, though occasionally my fingers fumble or code-rot occurs. Other useful materials Suggestions for learning R The R project is at : In particular, see the `other docs' there. Over and above the strong set of functions that you get in `off the shelf' R, there is a concept like CPAN (of the perl world) or CTAN (of the tex world), where there is a large, well-organised collection of 3rd party software, written by people all over the world. The dynamism of R and of the surrounding 3rd party packages has thrown up the need for a newsletter, R News. Library(help=boot) library(boot) ? But you will learn a lot more by reading the article Resampling Methods in R: The boot package by Angelo J. Ajay Shah, 2005.