Which three factors affect the price of a second hand car.

Richard Price 10B

Used Car Prices:

Coursework

Aim

The aim of this project is to decide which three factors affect the price of a second hand car. I will choose the three factors, which I think, will influence the price the most out of several lines of enquiry.

Introduction

I plan to investigate what factors influence the price of a second hand car. To begin with I had to look at a database of 100 cars. This database gave me a lot of information about each car (e.g. age, air con, mileage etc). All these factors were my lines of enquiry. To choose my three factors I had to decide which three of the eighteen factors would affect the price the most.

Lines Of Enquiry

There are a few lines of enquiries, which could be possible factors in affecting a second hand cars price. To choose my three factors I put all the lines of enquiry into a list from most important (1) to least important (18)

Mileage – This is my top factor because it tells you exactly how long the car has left in it. If the mileage is high it means the car has traveled far and may be in need of repair.
Age – This tells you how long the car has been running, if it’s been running a long time its parts may be worn from the rust and may need a repair.
Engine Size – Many people want a large engine, this may be because they want to go fast or maybe they live up a hill and want to make sure that it can go up without much trouble.
Style – The style is very important because it affects whether you want to buy the car or if it suits you.
Colour – Colour is important because if it is a horrible colour that doesn’t suit the car it might drop the price a lot.
Seats – If you have a large family, this is important if there aren’t enough seats you wouldn’t want to buy it.
Owners – This is a good indicator whether the car is good, if there has been a lot of owners there might be something wrong with the vehicle
Fuel – If you need a lot of fuel this could be important because some fuels are more expensive than others.
MPG – If the car does little miles per gallon then it will need more petrol and be more expensive to fuel.
Air Conditioning – Air conditioning is often looked as an extra feature but cars without can get stuffy.
Length Of MOT – If the MOT needs to be renewed soon, this is another thing that needs to considerated.
Tax – Tax is the same as MOT if it runs out soon its another thing you need to pay for.
Service – Service is expensive so if the car needs a service soon it might affect the price a bit, however I don’t think it will, as it is not that important.
Doors – Doors won’t really be a big factor, unless you need four doors and a boot.
Insurance group – This may affect the price but usually if you can afford a high priced car you can usually afford the high insurance group it might have.
Airbags – It is illegal now to have a car without airbags so this shouldn’t really affect the price.
Gearbox – Not many people look for the type of gearbox, I doubt this will affect the price.
Central Locking – This isn’t really a factor looked at by many people.

Hypothesis

I hope to see a positive correlation on the three graphs, which will prove that these factors do affect a price of a second hand car. I think this is the best way to approach the question because it will clearly show if these factors effect the price, if the factors do affect it, it will mean that the bigger the price reduction the bigger the age, the bigger the mileage and the bigger the engine. If this is correct I expect to see that the points on my graph will gradually get steeper from left to ...

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Hypothesis

Collecting Data For Random Sample (Method)

I got my data from the database of used cars, and I decided I would take 25 cars from the 100 in the database, to select these cars I had to be fair so I took every forth car in the list and would use that one. This is called a random sample of cars. This gave me totally random cars; in this way I kept the investigation fair. To see if this had any affect I will also take a stratified sample of cars. To obtain the % of price reduction I did this equation:

(Price when new – Price) x 100

Price when new

This equation gave me the % of price reduction, after doing this for every fifth car I drew up this table:

After drawing up this table I highlighted the two columns I wanted to draw a graph for and drew an xy scatter graph. I drew on a line of best fit myself, because a simple point which is way above the others, for example the engine size of 4 on car number 56, would have sent the line of best too high when I know that it was just a one off.

Collecting Data For Stratified Sample (Method)

It is important to do a stratified sample because one car make might be less desirable for second hand car dealers than another and therefore have dropped its price dramatically. So to keep it fair I had to choose the right amount of each car. For this data I had to draw up a frequency table showing all of the car makes. Once I had did this I had to work out how to select the right amount of each model to make a fair test.

To obtain the amount needed I had to take the number of cars in the database (100) and divide it by 4 to obtain the 25 which I wanted. So to obtain the amount needed for every model of car I divided the frequency of each car and divide it by 4. Then to keep the stratified sample stratified I picked the number of each car completely randomly. I did this by writing out all the numbers of the models I needed then put them into a hat, one model at a time and picked out the amount I needed. I did this so it was completely stratified. I then drew up a similar table for these stratified cars as I did for the random selection. For this table I also drew an xy scatter graph.

Conclusion

My results were what I expected, all of my three factors which I chose showed a positive correlation, this is where there is a sloping line of best fit starting from the bottom left and going towards the top right of the graph. The steeper the line of best fit the more affect the factor had on the line of best fit. As I did two different graphs for each factors there are some comparisons and differences to be made. The factor which affected the price the most in both samples was the mileage, however the line on my random sample was steeper than the one on my stratified sample. This is interesting because the stratified sample has a bigger average than the random sample but the reason why the random sample had a steeper best fit line was because all of its points were close together while the selected sample’s points were more dispersed. My age graphs were very similar but the selected sample’s line was just steeper. This was also indicated by the mean of both samples seeing that both said the mean age was 6. The engine size graphs were also very similar. Again the mean predicted correctly, it said both would be two. To make sure that my lines of enquiry were corrected I decided to take a line of enquiry that I thought wouldn’t affect the factor and do a graph for that, if my prediction was correct we should see that the line should be straight. My results were quite surprising for the stratified sample I found what I expected, no correlation. However for the random sample I found quite a big correlation. This is very surprising, but I think this is just a lucky coincidence because of two factors.

People don’t buy a car just because of its insurance group, when selling a car you don’t think that just because it has a high insurance group you should drop the price a lot.
The graph shows a correlation, however there are a lot of points well off the best fit line, this may suggest that this may be a coincidence.

Evaluation

This proves that the three factors I chose do affect the price of a second hand car. The order in which I put my top three lines of enquiry was also correct. So if you were selling a second hand car the age of the car the mileage it has done and the engine size will all drop the price of the car. To prove this was not just lucky I decided I would do one more graph against a factor, which I think will not affect the price and see if it has no correlation. I took the length of tax in months on the vehicle. The results I got confirmed that there was no correlation, which proves that age, mileage and engine size affect the price while the length of tax does not. However this investigation was done with only 25 cars to make a much more detailed conclusion I would of needed to take many more samples, to get the best result it would have been best to do it with all 100.

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