A paper which looks at ways in which quantitative data relating to comparative success rates of driving school instructors and test centres can be analysed, with some recommendations as to how qualitative data might be used to supplement this.
Name of Research Paper File: JL5_JLtest.rtf
Unformatted Sample Text from the Research Paper:
are the ultimate objectives of the study and the options available for collecting and analysing data. For example, one needs to consider the kind of data which is available and
how it is to be collected, as well as the use to which the results will eventually be put. It is also useful to assess whether or not the data
can be used for more than one purpose: in this instance, the primary outcome of data analysis will be to forecast which of the driving instructors are likely to have
the highest pass and fail rates in the future, but there are other applications in which the data could be useful, with regard to the relationship between driving schools, test
centres and learner drivers. In addition, having information regarding the comparative
competence of different instructors is also helpful in downsizing exercises and other matters relating to company structure and HR. However, the quantitative data which has already been collected may not
be sufficient to give a full picture of the situation as regards the capabilities of the different instructors. For example, it may be that on the basis of the data
provided instructor A has a far higher rate of fails over the period sampled that instructor B: on the face of it, this implies that A is more likely to
have a higher fail rate in the future. The quantitative
survey does not take into account the other factors which may have influenced the two individuals scores over the period concerned, since such data provides, in effect, only a fixed