By R. H. Baayen
A simple creation to the statistical research of language info, designed for college kids with a non-mathematical background.
summary: a simple creation to the statistical research of language info, designed for college students with a non-mathematical heritage
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Extra resources for Analyzing Linguistic Data : a Practical Introduction to Statistics using R
It is to be expected that non-native speakers require more time for a lexical decision. Furthermore, the conditions under which they make errors may differ as well. In order to explore this possibility, we make boxplots for the reaction times for correct and incorrect responses, and we do this for both the native speakers and the non-native speakers in the experiment. In other words, we use the factor NativeLanguage as a grouping factor. 9. As you can see, bwplot() requires two arguments, a formula and a data frame, lexdec in this example.
We use the same barplot() function as above. However, as our input is not a vector but a table, we have to decide what kind of bar plot we want. 5 illustrates the two options. xtabs. 3 Visualizing two or more variables In Chapter 1 we had a first look at the data of Bresnan and colleagues on the dative alternation in English. xtabs , RealizationOfRecipient = NP AccessOfRec AnimacyOfRec accessible given animate 290 1931 inanimate 11 99 new 78 5 , , RealizationOfRecipient = PP AccessOfRec AnimacyOfRec accessible given animate 259 239 inanimate 55 33 new 227 36 Such a contingency table might be visualized with a bar plot, but twelve bars or smaller numbers of stacked bars quickly become rather complex to interpret.
Of the histogram. As reaction time is a continuous variable, the density curve is both more appropriate and more accurate. Plotting the right panel is not difficult, but it requires some special care and illustrates some more details of how plotting works in R. 2, is that we have to make sure that the ranges for the two axes are set appropriately. Otherwise R will set the ranges to accommodate the first graph, in which case the second graph may not fit properly. We begin with the standard function for making a histogram, hist(), which, unlike truehist(), can be instructed to produce a histogram object.
Analyzing Linguistic Data : a Practical Introduction to Statistics using R by R. H. Baayen