By R. H. Baayen
An easy creation to the statistical research of language info, designed for college kids with a non-mathematical background.
summary: a simple advent to the statistical research of language information, designed for college kids with a non-mathematical history
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Extra info for Analyzing Linguistic Data : a Practical Introduction to Statistics using R
2. Calculate how many different texts are available in meta for each author. Also calculate the mean publication date of the texts sampled for each author. 3. Sort the rows in meta by year of birth (YearOfBirth) and the number of words sampled from the texts (Nwords). 4. Extract the vector of publication dates from meta. Sort this vector. Consult the help page for sort() and sort the vector in reverse numerical order. Also sort the row names of meta. 5. Extract from meta all rows with texts that were published before 1980.
The first step consisted of plotting the data points: > plot(ratings$Frequency, ratings$FamilySize) All we have to do is specify the vectors of X and Y values as arguments to plot(). By default, the names of the two input vectors are used as labels for the axes. You can see that words with a very high frequency tend to have a very high family size. In other words, the two variables are positively correlated. At the same time, it is also clear that there is a lot of noise, and that the scatter (or variance) in family sizes is greater for lower frequencies.
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. When you return to the same workspace, you will have to reload the packages that you used previously in order to have access again to the functions that they contain.
Analyzing Linguistic Data : a Practical Introduction to Statistics using R by R. H. Baayen