# Investigate the affect that age has on a car in terms of performance and structural integrity

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Introduction

GCSE statistics coursework

### Introduction

In this coursework I am going to investigate the affect that age has on the car. I am going to look at price, engine size, mileage, and age of the car. By the end of the coursework I am aiming to have a set of results about how the cars are affected by the age, price and mileage.

My hypothesis should state that

1. As the age of the car increases its price will decrease

2. The higher the mileage the lower the price.

I would meet this entire hypothesis by providing the diagrams below. For scatter diagrams I would be doing the line of best fit.

Plan

I am going to be collecting a sample of 100 cars.

- Box plots
- Cumulative frequency
- Scatter diagrams.

The reason why I am doing these diagrams is to give a clear understanding and also to give the reader a pictorial view about what is happening, and also I must say to get more accurate results. I would do each graph for each type of car and compare the results. After each of the diagram I would explain how I did the diagram. At the end of the coursework I would be doing a conclusion explaining what has happened and why. I have hosen 100 cars randomly fro the database instead of 1402 because I think it would cause inaccurate results. When I say randomly I mean I the cars that would give better results.

I am going to calculate the number of each type of car according to its age and mileage.

Middle

10

100001-110000

0

10

I have shown the above data on the graph above. This shows that my prediction was correct and as there are hardly any cars with a very high mileage and there are only a few smaller mileages.

For Vauxhall cars only

Mileage | Tally | Frequency | CF |

0-10000 | 0 | 0 | |

10001-20000 | 0 | 0 | |

20001-30000 | 4 | 4 | |

30001-40000 | 1 | 5 | |

40001-50000 | 2 | 7 | |

50001-60000 | 3 | 10 | |

60001-70000 | 1 | 11 | |

70001-80000 | 2 | 13 | |

80001-90000 | 0 | 13 | |

90001-100000 | 0 | 13 | |

100001-110000 | 0 | 13 |

As you can see I have provided another data for a different model of cars which shows my prediction is true. The reason why I am providing diagrams for different makes of cars is because to get more accurate results.

## Conclusion for tally charts

After my tally chart investigation I have provided mileage, frequency and cumulative frequency for different makes of cars to go into deeper investigation. I am aiming to go slowly my making different diagrams at different times so there would be no confusion, so therefore I would be going on to pie charts.

In my opinion I think that the cars with the most mileage would obviously belong to someone that drives very often or long distances. This could be sales man, who drives from one state to another. Therefore Fiat and Ford would belong to someone that drives their cars for long distances. Whereas the Vauxhall would belong to someone that does not drive long distances. This may belong to a person who does not like driving a lot.

The cars with the most mileage would also bring the second hand price down and will be decreased. Whereas the Vauxhalls that will have a lower mileage will have a higher second hand price rate than the Fiats and the fords.

Overall I cannot make a statement that which would tell me which car is suitable to buy. I shall now investigate further into different variables that affect the cars.

## Pie chart and bar chart

Make | Tally | Frequency | Cumulative frequency |

Fiat | 10 | 10 | |

Peugeot | 5 | 15 | |

Rover | 12 | 27 | |

Vauxhall | 13 | 40 | |

Ford | 16 | 56 |

Conclusion

### Analysis of Standard Deviation for all cars

### As you can see I have done standard deviation which has all the prices of cars and on X squared the price is times by itself to get that number. I would now describe a bit of how I done my standard deviation which is by first knowing about deviation from the mean, which is the difference between a particular value and the mean, is the deviation from the mean for that value. If you use x for the value and x for the mean then the deviation from the mean is x – x.

### The mean for the above standard deviation is:

### 1493274 divide by 100 = 14,932.74

### The standard deviation would be:

300036289522 divide by 100 = 300,362,895.5

As you see I have worked out the mean deviation and also standard deviation. The way that I have worked this out was that I applied to the formula that I have used above. In my opinion I found the standard deviation easy to work out but it took me very long to calculate the totals. I think this is very useful to me because it shows I have gone in to more investigation.

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

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