Download Statistics for Corpus Linguistics (Edinburgh Textbooks in by Michael Oakes PDF

By Michael Oakes

This ebook within the Edinburgh Textbooks in Empirical Linguistics sequence is a finished advent to the facts presently utilized in corpus linguistics. Statistical innovations and corpus purposes - even if orientated in the direction of linguistics or language engineering - usually pass hand in glove, and corpus linguists have used an more and more wide selection of information, drawing on suggestions constructed in a superb many fields. this can be the 1st one-volume advent to the topic.

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Statistics for Corpus Linguistics (Edinburgh Textbooks in Empirical Linguistics)

This ebook within the Edinburgh Textbooks in Empirical Linguistics sequence is a complete creation to the statistics at the moment utilized in corpus linguistics. Statistical strategies and corpus purposes - no matter if orientated in the direction of linguistics or language engineering - usually move hand in glove, and corpus linguists have used an more and more big variety of facts, drawing on strategies built in an outstanding many fields.

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1 The Pearson product-moment correlation coefficient The Pearson correlation coefficient allows one to establish the strength of relationships in continuous variables. If two experimental variables are plotted against each other on a graph, this is said to be a scatter plot. A straight line called the regression line can be drawn to fit the points on the graph as closely as possible. This straight line will move up from bottom left to top right if there is a positive relationship between the two variables, or down for a < previous page page_29 If you like this book, buy it!

If the variance between the samples is significantly greater than the variance within each group the results will suggest that the samples are not taken from the same population. It is first of all necessary to determine the overall mean of the entire data set, found by combining all the samples under investigation. The total variability of the entire data set is then the sum of the squares of the differences between the overall mean and each data item. Next, the variation between groups must be < previous page page_22 If you like this book, buy it!

If there are N scores contributing < previous page page_12 If you like this book, buy it! next page > < previous page page_13 next page > Page 13 to a given mean value, only N-1 of them are free to vary since the other one is constrained to contribute just enough to the value of the mean. For example, if we have three variables with a mean of 10, we can select any values for the first two variables (a and b), but the third value is constrained to be 30-(a+b) if we are to maintain our mean of 10.

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