Bivariate Data Exploration
Aim:
The aim of this investigation is to see if there is a correlation
between the engine size of a car and the insurance group that it
resides in.
Introduction:
In our present day there is an ever-increasing public demand for
value-for-money products and services, especially in cars, shopping
and clothing markets. For students, this is even more important as
everything they buy (unless they are particularly affluent) can easily
amount to debt (through extensive student loans). For students in
particular, cars are very often an essential means of transport, and
so, like most things, it is important for a student to get the best
deal for their car.
However, insurance companies and car dealers are very much aware of
the student situation and have classified certain cars as ‘student
carsÂ’, and to clarify this, include cars from Peugeot (106, 306),
Renault (Clio), Citroen (Saxo), and Vauxhall (Nova) to name but a few.
Now it seems that these cars all have relatively low engine sizes,
commonly ranging from 900-1800cc, and are all placed in relatively low
insurance groups (and therefore have lower insurance costs), but this
may not be the case for all cars, especially those with larger engine
sizes.
This investigation will examine data from a range of cars, varying in
both engine size and insurance group, and if a positive correlation is
found between insurance group and engine size, then the concept of
‘student cars’ will not be such a worrying factor when a student goes
to buy his first car, however if there is no correlation then it is
entirely possible that insurance companies are charging too much for
cars in the ‘student car’ category.
Data Collection:
To start the investigation, data needed to be collected before any
conclusions could be made. A local used car showroom was approached,
and data from all cars on their forecourt (and in the showroom) was
collected. This data was taken directly from the records that the
The author has employed the use of qualitative data in order to draw out and support his ultimate conclusions. The author has used several types of data sources, including the BSI data system. The BSI is described as a “problem based policing strategy for data collection.”
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