• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

The aim of this project is to investigate which factors influence the costs of second hand cars. The makes we were looking into include Ford, Peugeot, Renault and Vauxhall.

Extracts from this document...

Introduction

Write Up

The aim of this project is to investigate which factors influence the costs of second hand cars. The makes we were looking into include Ford, Peugeot, Renault and Vauxhall.

To aid us with our research, we were given a bank of secondary data of one hundred and ninety nine cars. Along with these cars, we were given nine variables for each car; colour, engine size, petrol/diesel, year of manufacture, mileage, cost, preliminary cost, make and model. We later had to add an age column for each.

We have been asked which features make most difference. My predictions for which makes the most difference are as follows:

FACTOR                                IMPORTANCE                RANGE

  1. Age                                most important factor                1yr-16yrs
  2. Mileage                                                                1200-150,000image00.png
  3. Cost                                                                 375-132,500
  4. Petrol/Diesel                                                        Petrol/Diesel
  5. Engine size                                                        1,000-2,500
  6. Year                                                                1989-2002
  7. Model                                                                106-Vectra
  8. Make                                                                Ford-Vauxhall
  9. Preliminary Cost                                                        6,000-20,020
  10. Colour                                least important factor                Black-Yellow

Looking through the data, I can see that it is not perfect. There are many missing fields of data, and I had to remove one rogue piece of data, being a Renault Laguna. I knew it was not right from my general knowledge of cars, the price being too high.

I will draw up scatter graphs, histograms and cumulative frequency curves (for cost compared with the whole population’s age followed by individual Makes)

to try and distinguish any correlation’s (patterns) in the cost distribution.

...read more.

Middle

What I think will happen is-image01.png

As age increases,      the cost will decrease.image02.png

This is because there is a very strong correlation between these factors. I will look at one model for one example because if I look at a group of similar cars, I can be confident that any observations I make are because of the cost and not anything else. For this model, I draw a scatter graph of cost against age.

For this scatter graph, I put Age on the X axis and Cost on the Y axis as Cost depends on Age. This makes Cost the dependent variable. I also included a line of best fit and an R2 measure of correlation where R=1 is a perfect correlation.

On examining this graph, there’s a very strong negative correlation between cost and age. Based on these findings, I can easily make my first hypothesis:

There is a fairly strong correlation between Cost and Age.

2nd Hypothesis

I am now going to investigate the variable that I believe would be next important in determining the second hand cost. This is Mileage. I think that like the age variable, there may be a sign of negative correlation between Mileage and Cost. Like before, I will make scatter graphs based on each make of my sample, except this time it will be for Mileage and Cost.

...read more.

Conclusion

These estimates are only moderately reliable as the correlation between cost and age is only moderately strong. Based on this analysis of my sample (which was a reasonably good representation), I believe I have evidence to support the first hypothesis.

There are clearly other factors influencing the cost, so I will now move on to mileage. Firstly, I will draw box plots for mileage. From these I can see that on average, Ford cars have the lowest median. This seems strange as they were the oldest on average.

Vauxhalls are the most spread out which fits in with that age being spread out. I will now draw a scatter graph for the sample and for each make. I believe that on the whole, these broadly confirm my hypothesis. The whole sample shows a weak/moderate negative correlation.

It seems to me that I was correct. My initial prediction that age is the most important variable, but mileage is also important was true. The next thing I am going to do is indicate on the cost against age scatter graphs for each make, the mileage for point and the engine size to see if this gives me any insight into the influence of mileage or engine size.

Having looked at these, I don’t see a very clear pattern. Although, on average, cars with a lower mileage have higher prices, but as always, there are exceptions.

...read more.

This student written piece of work is one of many that can be found in our GCSE Gary's (and other) Car Sales section.

Found what you're looking for?

  • Start learning 29% faster today
  • 150,000+ documents available
  • Just £6.99 a month

Not the one? Search for your essay title...
  • Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

See related essaysSee related essays

Related GCSE Gary's (and other) Car Sales essays

  1. What factors influence the price of a second hand car

    15800 5999 2 33000 62.03 Fiat 6009 1995 6 20000 66.80 Rover 13586 3795 6 49000 72.07 Nissan 6295 1795 8 47000 71.49 Daewoo 11225 5999 3 42000 46.56 Rover 8595 2495 6 33000 70.97 Ford 8785 1595 7 68000 81.84 Fiat 6864 1495 8 51000 78.22 Rover 6645 895

  2. I will research the cars by putting the data I have been given into ...

    The pie-charts show that black and silver cars have more cars below average depreciation than any other colour which means that they depreciate slower compared to red which has a lot of cars with above average depreciation. The graph showing price against age was chosen as I found that this was the largest factor of depreciation on the cars.

  1. Maths Coursework:Used Cars

    0 <2000 5 <3000 2 <4000 3 <5000 2 <6000 0 <7000 0 <8000 2 <9000 2 Price Less than � CF <1000 1 <2000 2 <3000 3 <4000 4 <5000 0 <6000 0 <7000 1 <15000 1 Using the information in the table and graphs I can find the lower quartile, median and upper quartile.

  2. I have been given instructions to collect data for my GCSE statistics coursework and ...

    price of the car, you will have to compare two of the cars with the same make. Example, looking at the rover, it has a 2.3 engine at 6999. But looking at the other rover, it has a size of 1.6, but is only 4995, this could mean that the engine size does affect the price of the car.

  1. Statistic coursework-what has the most influence on the price of a second hand car?

    The range of Ford is 14000 and for Mercedes are 35000. The range for Mercedes is 150% higher than Ford. This is the formula I used to work out the percentage for how much higher the range is for Mercedes than Ford.

  2. Used Cards - find which factors will influence the price of a second hand ...

    Sometimes, the entire population may be sufficiently small, and I could have included the entire population in the study. However since the data provided was too much to utilize, I will have to apply a sampling to my data. I will carefully choose the sample which can be used to represent the population.

  1. Legal and Ethical Analysis of Ford Pinto

    Practical considerations dictated the Pinto's fuel tank placement. The fuel tank could not be placed over the axle due to the possibility of introducing other Pinto variations such as station wagon or hatchback. The over the axle location also would greatly reduce storage space and reduce serviceability.

  2. Used second hand cars

    If a particular make is found to be the top stylish car then the price of the second hand would also be higher. Data Collection: Due to the fact that the information in the data has been provided from recent adverts and reputable guides to the motor trade, it obviously cannot be unreliable.

  • Over 160,000 pieces
    of student written work
  • Annotated by
    experienced teachers
  • Ideas and feedback to
    improve your own work