Analyzing Linguistic Data : a Practical Introduction to by R. H. Baayen

By R. H. Baayen

An easy creation to the statistical research of language facts, designed for college kids with a non-mathematical background.

summary: a simple creation to the statistical research of language info, designed for college kids with a non-mathematical heritage

Show description

Read or Download Analyzing Linguistic Data : a Practical Introduction to Statistics using R PDF

Best research & publishing guides books

The Handbook of Creative Writing

An in depth, sensible and inspirational source, this three-in-one quantity is designed as a textbook for college kids and practitioners of artistic writing in any respect degrees. In forty eight special chapters the guide: *examines the serious theories in the back of the perform of artistic writing (Part 1) *explains the fundamentals of the way to write down a singular, script or poetry (Part 2) *explores tips to take care of the practicalities and difficulties of turning into a author (Part 3).

Land's End: A Walk in Provincetown (Crown Journeys)

During this occasion of 1 of America's oldest cities (incorporated in 1720), Michael Cunningham, writer of the best-selling, Pulitzer Prize–winning The Hours, brings us Provincetown, the most idiosyncratic and outstanding cities within the usa, perched at the sandy tip on the finish of Cape Cod.

The Hidden Europe: What Eastern Europeans Can Teach Us

Francis Tapon yearned for a ecu experience, yet Western Europe appeared too tame and passe. So he traveled for three years vacationing each japanese ecu state all 25 of them. The Hidden Europe cleverly mixes insightful proof with hilarious own anecdotes. it truly is profound, but mild. Francis Tapon is a pointy observer who is helping you distinguish a Latvian from a Lithuanian, whereas now not complicated Slovenia with Slovakia.

Additional resources for Analyzing Linguistic Data : a Practical Introduction to Statistics using R

Example text

Its first argument is the numerical vector for which we want averages according to the subsets defined by the list supplied by the second argument. 673333 As aggregate() does not retain the original names of our data frame, we change the column names so that the columns of heid2 remain easily interpretable: > colnames(heid2) = c("Word", "MeanRT") In the averaging process, we lost the information about the base frequencies of the words. We add this information in two steps. We begin with creating a data frame with just the information pertaining to the words and their frequencies: > items = heid[, c("Word", "BaseFrequency")] Because each subject responded to each item, this data frame has multiple identical rows for each word.

Extract from meta all rows with texts that were published before 1980. 6. Calculate the mean publication date for all texts. The arithmetic mean is defined as the sum of the observations in a vector divided by the number of elements in the vector. The length of a vector is provided by the function length(). Recalculate the mean year of publication by means of the functions sum() and length(). 7. frame(Author = c("Cela","Mendoza","VargasLLosa"), + Favorite = c("Stravinsky", "Bach", "Villa-Lobos")) > composer Author Favorite 1 Cela Stravinsky 2 Mendoza Bach 3 VargasLLosa Villa-Lobos Add the information in this new data frame to meta with merge().

9. As you can see, bwplot() requires two arguments, a formula and a data frame, lexdec in this example. The formula, RT ∼ Correct | NativeLanguage considers RT as depending on the correctness of the response (Correct), grouped by the levels of NativeLanguage. In the formula, the vertical bar (|) is the grouping operator. Another way of reading this formula is as an instruction to create box and whiskers plots for the distribution of reaction times for the levels of Correct conditioned on the levels of NativeLanguage, the groups of native and non-native speakers.

Download PDF sample

Rated 4.03 of 5 – based on 17 votes