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Used Car Sales Plan

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The aim of this coursework is to investigate and find out data about a particular subject and then show that the data collected can be presented and compared in many ways using different types of tables, charts and graphs.

I am going to be looking at used car sales for my coursework. I will specifically be looking at the mileage and age of used as I think that these are the most relevant variables that will affect the value of used cars, other variables that could be used are;

o New price

o Engine size

o Colour

o Age

o Make

o Model

o Fuel (diesel/unleaded)

To find out how the mileage and age affects the price, I will need to find a wide range of cars that have a wide range of mileages; this information is already available to me from the master spreadsheet provided by the school.


I predict that as the mileage of used cars increases, it will directly affect the car by decreasing its value, as the age of cars increases I believe that it will also affect the value of the car by a decrease. I will show this by putting the data into scatter graphs.

Using lines of best fit should prove my theory, but I have come across problems with this as it shows negative values, like negative mileage, age and price. There may be some problems as some cars may increase in value as they age and gain higher mileages, these will show up as anomalies on my scatter graph and I will be able to discard this data. I will also use pie charts to show the different proportions of age, mileage and prices of used cars.

Problems that may occur;

o Master spreadsheet may not have the needed information for my investigation.

o The decrease in price may be affected by other variables; this could affect my results and cause them to be inaccurate.

o I may not have enough time to use computers.

Collection of data

I have selected the data that I need from the master spreadsheet already available to me from the school; I selected the age and mileage of ninety-seven cars. I have put this data into scatter graphs, one for age against price and one for mileage against price, I used trend lines to easily compare the data. I have used quite a lot of data, this should help me to obtain accurate results and show good trends on my charts and graphs. The trend lines will show the anomalies and trends clearly so that I can easily discard unusefull data. I have also created a pie chart to show the proportions of the age of the used cars; the reason for this is that use can clearly see the percentage of certain ages of cars.


I can conclude that my hypothesis was correct in saying that the value of used cars would decrease as their age and mileage increased. From the results I have obtained I can conclude that age and mileage affect the value/price of cars in very similar ways. Both age and mileage affect the value of the car usually in a decrease. My charts and graphs show me that age is directly proportional to price of the cars, as is the mileage. As I said in my plan some cars can increase in value as they age. The trend lines on my graphs are all very similar this proves that age and mileage both affect the value of used cars in similar ways.

My scatter graphs show mileage and age plotted against price, the reason for me using curved lines to show trends instead of straight ones is because I found that straight lines showed negative values for all three variables, price, age and mileage. The reason for using scatter graphs is because they show the trends most clearly; anomalies can be discarded as the stand-alone.

I made a line graph to show the difference in price of all of the cars when new and when used, it shows that they all decreased in value.

The pie chart that I created shows the proportions of the different ages of the used cars, I used a pie chart because it shows the different proportions most clearly.

I made cumulative frequency graphs for the cars and there mileages, I used inter quartile ranges so that I could develop box plots and to eliminate anomalies. I also used cumulative frequency graphs to find trends in the ages of the cars; I then used this data to create box plots.

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