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