Download e-book for kindle: AMD AM29116 Microcoded Instruction Processor by R. Anderson

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However, it is also useful from the technical 'design' point of view to think of it as one group of people quantified on two variables'social class' and 'amount of [-in] pronunciation of -ing'. The investigation as a whole then comes down to a matter of looking to see if there is in fact a relationship between the two variables. Do people who are categorised a particular way for 'social class' tend also to score in some particular way for 'amount of [-in] pronunciation of -ing'? Or more concretely, do the working class informants really use [-in] more?

A useful way of getting an overview of ways of data gathering as part of what is necessary to arrive at quantifications of linguistic and other variables is to look at them in four general categories. By way of introduction, I shall first give an example of each type of technique applied to measuring the 'same' phenomenon. Suppose we want to quantify the preference of speakers of English for saying or writing needn't/need not as against doesn't need to/don't need to. In terms of specification of what variable is being measured, we are in the realm of the measurement of a feature of the grammatical production < previous page page_32 next page > < previous page page_33 next page > Page 33 performance of normal adult native speakers, for whom both types of negation, with or without do, are clearly possible.

There are a number of wellknown terms that I might have used instead of the cumbersome periphrases for techniques 1 to 4, but all are used so variedly by different people that it is hard to pin them down. I shall now say a word about some of these. Observation might be used for the more naturalistically based data gatheringespecially for my 1and is sometimes opposed to 'testing'. However, all quantification, however artificial, really has to be said to involve some sort of observation of characteristics of cases.

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AMD AM29116 Microcoded Instruction Processor by R. Anderson


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