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Investigate what affects the used price of a car.

Extracts from this document...

Introduction

Zeta Blakeley Statistics Coursework I am going to investigate what affects the used price of a car. I have been given a spreadsheet by my teacher containing 204 cars of various different makes and models with information such as; mileage, age, new price, used price, engine size and colour. I am planning to investigate some factors like age, mileage, and make. To do this I am going to draw 2 comparative pie charts, tables and scatter diagrams. I will look for correlation, or anything that stands out. I am also going to use Spearman's Rank Correlation Coefficient to find the strength of the correlation. I will come to a conclusion and look to improve. Hypothesis 1 "The make/type of a car does affect the used price". To prove this hypothesis I have sampled a population of cars in the spreadsheet given to me by my teacher. I have chosen to take all of the fords and all of the Mercedes because these two groups have the most substantial amount of cars, using all of the cars under these groups for they are a reasonable amount to test yet I have excluded three cars; one Mercedes because it has no used price in the spreadsheet, and two Fords because one is missing the used price and the other is missing a new price. ...read more.

Middle

I'm going to investigate if the second hand price of a car is affected by its age. I am going to use 25 cars to produce a scatter diagram. My scatter diagram will have age on the x axis and the used price on the y axis because the price is being affected. I will use only fords so my data isn't bias against different makes of cars. When selecting my data I decided not to use all of the fords because I didn't want my scatter diagram to be to busy and hard to read, so I used random sampling so every car has an equal chance of being used. I did this by using the same method that I used in hypothesis 2. I predict that my scatter diagram will have a negative correlation because I think the younger the car the higher the cost. I drew my line of best fit by using (x, y). Where I worked out that the mean age was 7.92 and the mean price was �3479. So my line of best fit will go through the point (7.92, 3479). My Scatter diagram shows: * There is a negation correlation * It is a weak/moderate correlation * There are no obvious anomalous results I can use the line of best fit to make predictions. ...read more.

Conclusion

I took random samples and produced scatter diagrams and found that in the samples I took the scatter diagrams produced did not back up my hypothesis although could be improved by using more controlled variables such as the model. My second hypothesis was "The larger the mileage the cheaper the used price of a car". I again took a random sample and produced scatter diagrams, this time I found that my hypothesis was right. My final hypothesis was "The older the car is, the least expensive the used price". I took more random samples and produced scatter diagram, and I also use SRCC to find the strength of the correlation. I found that my hypothesis was right. If I was to re-do my coursework to make it better I would use primary data as the spreadsheet I was given could have gone out of date and isn't as reliable as primary. I would also use better sampling techniques such as quota because then it would have been a fairer test. As well to improve I could use larger samples, which will make my work more precise and reliable and will also help with investigate a larger population. ...read more.

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