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Essay / Research Paper Abstract
This 5 page paper considers a case study provided by the student where a union is making a claim for an increase in the pay of its members as they are receiving less than a other set of staff with equivalent jobs. The writer uses the data provided; a random set of salaries from the two groups of staff and shows how a statically analysis may take place, and then gives the management advice on the best way to proceed. The bibliography cites 3 sources.
Page Count:
5 pages (~225 words per page)
File: TS14_TEwagest.rtf
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Unformatted sample text from the term paper:
are several assumptions that need to be made. There is a comparison between a random sample of fifty sales staff and fifty administration staff, in order to considers this we
will make the assumption that there is not a sliding scale of payments made according to age, and that the random sample in both instances is a fair representation. However,
we need to caution that a random selection may not be representative of the entire staff, and as such results may be skewed. The union are making a claim for
higher wages as a result of the perception that the administration staff are receiving higher wages. In order to ascertain this we can look at the statistical analysis if the
wages of the two different groups. Firstly, we will look at the wages of the sales staff and examine what the sample of fifty shows us. We can then look
to the administration staff, and compare the two before making recommendations. The sales staff of fifty have a range of wages from 83.62 to 164.82. The wages appear to be
relatively well spaced, with each quartile having a wide range, however, the bottom quartile has a lower range that the top quartile.
The first measure we can look at is the average. the arithmetic mean, which is usually referred to in the shortened form of the mean (Curwin et al, 1996).
This is what is commonly known as the average, the values of the data are added together and then divided by the number of values which were totalled (Curwin et
al, 1996). The mean can be used with most sets of data, but is not necessarily suitable to be used with all
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