By Michael Oakes
This publication within the Edinburgh Textbooks in Empirical Linguistics sequence is a complete advent to the information presently utilized in corpus linguistics. Statistical thoughts and corpus purposes - no matter if orientated in the direction of linguistics or language engineering - frequently move hand in glove, and corpus linguists have used an more and more wide array of facts, drawing on strategies constructed in a very good many fields. this can be the 1st one-volume advent to the topic.
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Extra info for Statistics for Corpus Linguistics (Edinburgh Textbooks in Empirical Linguistics)
Sample text
5 is subtracted from each value of O if it is more than E. In a one-way design experiment, we are comparing the relation of Frequencies for a single variable such as part of speech. The number of degrees of freedom is the number of cells in the frequency table minus one. In a two-way design we compare the relation of frequencies according to two different variables, such as part of speech and genre. The degrees of freedom is , if we have m levels for the first variable and n levels for the second.
For example, one cannot compare groups A and B, A and C, then B and C. An attempt to use the t test for such comparisons will make it artificially easy to reject the null hypothesis. 4) should be used for such comparisons. An assumption of the t test that relates to the normal distribution is that the data is interval-scored. It is also assumed that the mean and standard deviation are the most appropriate measures to describe the data. 3. 3 has been obtained from a corpus of learners' English. The number of errors of a specific type occurring in each of 15 equal-length essays are shown; eight produced by students learning by traditional methods (the control group) and seven produced by students learning by a novel method that we wish to evaluate (the experimental group).
A sample can be taken as representative of a population only if it is a random < previous page page_9 If you like this book, buy it! , a sample chosen in such a way that every possible sample has an equal chance of being selected. One method of sampling is called spread sampling, which requires the selection of small samples (taken, for example, from a corpus of text) at different starting points. The starting points of the samples are randomly chosen, perhaps by using a table of random digits.