Download Quantitative Methods in Linguistics by Keith Johnson PDF

By Keith Johnson

Quantitative equipment in Linguistics bargains a realistic advent to stats and quantitative research with information units drawn from the sector and assurance of phonetics, psycholinguistics, sociolinguistics, old linguistics, and syntax, in addition to chance distribution and quantitative tools. offers balanced therapy of the sensible points of dealing with quantitative linguistic info comprises pattern datasets contributed by way of researchers operating in various sub-disciplines of linguistics makes use of R, the statistical software program package deal most typically utilized by linguists, to find styles in quantitative info and to check linguistic hypotheses contains student-friendly end-of-chapter assignments and is observed through on-line assets at www.blackwellpublishing.com/quantmethods.

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The question is, how different is different enough? We can quantify the difference between the sample mean and the hypothesized population mean in terms of a probability. 7 or less. 7 mean coming from a population that has a mean of 100 ms is pretty darn low - so we reject the hypothesis that ~ = 100 (let's label it Ho), and instead accept the alternative hypothesis that ~ < 100 (call this HI and note that this is only one of several possible alternative hypotheses). 2 The decision to accept or reject the null hypothesis may be wrong in two ways.

2). A type 11 error occurs when we incorrectly accept the null hypothesis. Suppose that we test the hypothesis that the average VOT for Cherokee (or at least this speaker) is 100 ms, but the actual true mean VOT is 95 ms. If our sample mean is 95 ms and the standard deviation is again about 35 ms we are surely going to conclude that the null hypothesis (Ho: ~ = 100) is probably true. 706. 08 testing for a small dl·fference Nonetheless, by accepting the null hypothesis we have made a type 11 error.

Toll=F) Our sample estimates of the means are easy - ;\\971 and X2001 are the least squares estimates of these parameters. What is our estimate of the standard error of the mean? 5034847 In this function call I specified the degrees of freedom of the numerator (n 2OO1 1 25) and of the denominator (111971 1 17) for the two estimates of variance that went into the F-ratio. I also that we are looking at the upper tail of the F-distribution because, as is usually done, I put the larger of the two variances as the numerator.

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