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

By R. H. Baayen

An easy advent to the statistical research of language information, designed for college students with a non-mathematical background.

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

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

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The smoothing function that we used here is lowess(), which takes as input the X and Y coordinates of the data points and produces as output the X and Y coordinates of the smooth line. To plot this line, we fed its coordinates into lines(). The basic idea underlying smoothers is to use the observations in a given span (or bin) of values of X to calculate the average increase in Y . You then move this span from left to right along the horizontal axis, each time calculating the new increase in y.

Packages that are installed but not loaded automatically can be made available by means of the library() function. packages(), or through your graphical user interface. The MASS package contains a wide range of functions discussed in Venables and Ripley (2003). We make the functions in this package available with: > library(MASS) All the functions in the MASS package will remain available to the end of your R session, unless the package is explicitly removed with detach(): > detach(package:MASS) When you exit from R, all of the packages that you loaded are detached automatically.

The function lines() takes a vector of x coordinates and a vector of y coordinates, and connects the points specified by these coordinates with a line in the order specified by the input vectors: > lines(d$x, d$y) In this case, the command lines(d$x, d$y) is unnecessarily complex, as a density object such as d tells plotting functions like lines() where they can find the x and y coordinates. Therefore, all we actually have to specify is: > lines(d) You can plot a histogram or density object simply with the general plotting function plot(), > plot(h) > plot(d) without having to specify the x and y values yourself.

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