GCSE: Gary's (and other) Car Sales
Meet our team of inspirational teachers

I have been asked to investigate factors that affect the depreciation of cars.
This filled the box with the age of the car. I then highlighted the box, right clicked and selected copy, before highlighting all the boxes below and selecting paste special, formula. This filled in the ages for all of the cars. Next, to get the percentage depreciation, I made another column and filled it with a more complicated formula =(I2H2)/I2*100 where I2 is the price when new and H2 is the price now. This filled the first box in the percentage depreciation column with the appropriate value, and I copied the formula into the other boxes as before.
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Objective; to investigate the relationship between used car price and age of car.
Sampling; (Planning) My plan involves selecting 40 cars from the total of 100 cars by car in the list. To do this I used stratified sampling which involved taking a tally of all the cars arranging them in sections depending on their age, then as 40/100 is 0.4 I multiplied the frequencies for each age group by 0.4 and rounded it to the nearest integer where the total would add up to 40 cars. I decided to leave out the cars of ages 11+ since their was only a maximum of one car for each year ,hence when I multiplied by 0.4 and rounded to nearest integer I got 0.
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The aim of this experiment is: To observe how differences from car to car effects the second hand value e.g. colour, make, mileage, engine size length of MOT and the number of seats.
Stratified random sampling this is obtained by separating the data in to appropriate categories called stratas e.g. by mileage. Then find out what percentage of all the data Is in each strata then selecting a random sample form each sample in proportion to its size. * When the data is chosen by whichever method it will be placed in a table an then represented on a graph the graphs I will use are: scatter graph, cumulative frequency curve. * On my scatter graph I will work out and draw the line of best fit going through the mean and work out the least squares regression line, standard deviation, and the spearmans rank correlation coefficient all these methods will be explained further in my explanation page.
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In this project we have been given a large amount of data on used cars to work with, and our aim is to analyse this and investigate any possible correlations between cost and other factors given.
Here I have simply taken all the Vauxhall cars from the list given, and taken the most basic statistics required: Car Number Make Model Price when New Current Price Mileage 3 Vauxhall Vectra 18580 7999 20000 4 Vauxhall Astra 14325 6595 30000 10 Vauxhall Tigra 13510 7499 27000 12 Vauxhall Vectra 18140 6499 49000 14 Vauxhall Corsa 8900 4995 24000 26 Vauxhall Nova 5599 1000 75000 47 Vauxhall Astra 13740 2900 58000 84 Vauxhall Corsa 7840 4976 21000 85 Vauxhall Corsa 7440 3495 55000 93 Vauxhall Calibra 18675 6995 63000 97 Vauxhall Astra 9795 3191 43000 100 Vauxhall Vectra 13435
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What factors effect the Price depreciation of a car and how?
To do this I will use the random button on my calculator. I will pres it twice: first time I will take the last two digits for the page number and then I will press it again and use the last 2 digits for the car number in the page. If there is no such page or car then I will repeat the procedure. I am using Random Sampling because since I don't get told what order the cars are in.
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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 try and distinguish any correlation's (patterns) in the cost distribution. Fortunately, the median is not affected by extreme values so the box plots will be fine, as will any other cumulative frequency curves. Most variables would affect the cost, but by how much remains to be seen. I am now satisfied that results from my sample will represent the population as a whole. 1st Hypothesis I have said that age is the most important factor and so I will try to explore it further.
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This piece of coursework is designed to test the use and interpretation of statistics in relation to used car prices.
I predict that the mileage of a car will make a considerable difference to the price of a car, as the higher the mileage, the less value the car will have. 4. The number of owners that a car has had may also cause a decrease in value as the condition of the car may vary. 5. Finally, I predict that the extra features of a car, e.g., air conditioning, central locking, etc. will also boost the price of a car.
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The aim of this coursework is to find out what the different factors are that affect the value and price of different cars
However older cars are less likely to include these features so the price will decrease more. The make of car could also influence the price because people pay different amounts for various makes of cars. The three variables I have chosen to analyse are the age, the mileage and the engine size of the cars. I will then do comparisons on different makes of cars. Summary of Data: In the age data there are four anomalies. They are the Bentley Turbo R, Porsche Sport, Mercedes Elegance and Rolls Royce Silver Spirit.
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Statistics on car prices
2 litres, the type of fuel the car uses e.g. diesel or unleaded, the MPG (miles per gallon) this is roughly how many miles the car can travel at a constant speed on one gallon of fuel, the current mileage of the second hand car, if it has a service history or not, the number of previous owners, the length of the current MOT (road tax) if there is one, the TAX months, its insurance groups (this relates to the prices the owner will have to pay to insure the car, e.g.
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My maths coursework is based on a spreadsheet with information about cars.
Collecting, Processing and Representing I have collected the required data and sorted it into tables. All the cars which are 1 year old are shown below. I have worked out the mean; this will be used in the final chart which will compare all of the ages. Age Price 1 7999 Total 1 10999 98832 1 6795 Average 1 7500 9883 1 7500 1 7995 1 14999 1 13995 1 13500 1 7550 The two year old cars are shown below.
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Investigation of factors that effect the price of a car.
Mercedes may not be owned by that many people because it is a prestige car and has all the qualities, it still holds its price. The reason for car ownership could be that the Mercedes might not be affordable because it is too expensive for some people or isn't affordable. After doing so and once I have examined the factors affecting each of those cars than I will do frequency charts and Cumulative Frequency graphs on age, mileage and price for each one of those 3 selected cars.
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My maths coursework is based on a spreadsheet with information about cars. I am going to study the data and answer the question  In general does the age of second hand cars affect the price?
Collecting, Processing and Representing I have collected the required data and sorted it into tables. All the cars which are 1 year old are shown below. I have worked out the mean; this will be used in the final chart which will compare all of the ages. Age Price 1 7999 Total 1 10999 98832 1 6795 Average 1 7500 9883 1 7500 1 7995 1 14999 1 13995 1 13500 1 7550 The two year old cars are shown below.
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What affects the price of second hand cars?
Then I'll need to put all this data into tally charts. Then I'll make graphs out of the tally charts. I'll be using frequency graphs to look at peak and spread and I'll use Scatter graphs to find relationships between data. I will analyse these graphs and see how useful they are at answering my question. I will also turn my results into averages and then compare the averages to see which of my lines of enquiry effects the price of a second hand car the most.
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Used Car Prices
I could use scatter diagrams again, which would make it an easier comparison to my initial set of results. Alternatively I could use a cumulative frequency graph which will also help me find the median and interquartile range.  After I have collated the data I will try and find a general formula for the depreciation of car prices.  I will then set about refining my investigation to find a more accurate formula. I can do this by concentrating on a specific type or model of car or maybe even combining some of the features.
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Use the information to investigate what influences the price of cars.
at the very beginning or at the end. I will also use the exact same cars for each three hypotheses. Hypothesis 1  The price of second hand cars will decrease with age. Hypothesis 2  The price of second hand cars will increase with engine size. Hypothesis 3  The price of second hand cars will decrease with the amount of mileage it has done. I will compare the two pieces of data in the hypotheses to either prove or disprove the hypotheses. I will use standard deviation, graphs and other equations to show the methodology and findings of the hypotheses.
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The aim of our coursework is to investigate the effect of different variables on the price of a second hand car.
3. I predict that the price of a used car is dependant on mileage. This is because as the mileage of a car increases, the car becomes less desirable. Also as the mileage increases so does that age of the car. This increases depreciation and so I expect there to be a positive correlation between mileage and percentage decrease in price. In order to prove or disprove the above hypotheses I will be using a stratified random sample as shown below. This sample was created by choosing a sample size of 25, as it is divisible by 100.
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The aim of this investigation is to find out what influences the price of used cars (second hand). Used cars usually cost less than brand new cars, but this can be affected by hypotheses' such as mileage, age, colour, how it has been used etc.
Ford) is higher than less common cars (i.e. Mercedes) Testing hypotheses one. I'd expect to find negative correlation. But vintage cars might be worth more as they get older. Good condition old cars might be worth more when older. New cars that are written off might be worth less than others of the same age. The way I am getting my random samples, for this hypothesis, is by using my calculator because the human mind is unable to select things randomly. I do this by tapping the second function key on my calculator and then pressing the random key.
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In my investigation I will be trying to find out the average loss of money from 1st hand, to 2nd hand as the age of the car go up.
What I had too do is only look at two or three things and I had too look at the closely and I would had to compare something to another thing or why something changes. Like when you do more miles in the car the car price goes down and I would have to find an explanation for that. Aims Here I am going to be looking at the different sorts of colours of cars. What I wasn't to find out is which colour is the most popular out of all of them.
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My task for this coursework was to analyse the data given to me to see what effects the price of a second hand car; I tested such ideas like, age, service history and M.P.G.
Ford Escort 7 Ford Fiesta 8 Ford Fiesta 11 Ford Fiesta lx 7 Ford Escort duet 7 Ford Escort 5 Ford Escort 5 Ford Fiesta 4 Ford Focus 2 Ford Puma 3 Ford Escort 7 Ford Mondeo 4 Ford Fiesta 10 Ford Escort 5 Ford Escort 6 I plotted a scatter graph of my findings and found out that there is a positive correlation between the age of a car and the amount of % the car value has decreased. This shows that as the age of the car goes up the more percent is lost of its original value.
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My task for this piece of coursework is to statistically analyse the data for used car sales. I will use the information that was given to me, to investigate what influences the price of a secondhand car.
If the mileage is low, the selling price is likely to be higher. * Engine capacity: The engine capacity is very important. The higher the engine capacity, the faster the car. Most people would like to have a fast car rather than a slow one. The price is likely to increase if the engine capacity is high. * Colour of car: The colour is likely to be important as different owners are likely to have different tastes in colour, but I do not think that the price will increase. * Condition of car: If the car is in good condition, inside and outside, it is likely to last longer.
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What influences the price of a second hand car.
Model Price Price Difference Age Model Price Price Difference Age New Old New Old Vectra 18580 7999 10581 2 Orion 16000 7999 8001 1 Astra 14325 6595 7760 4 Escort 8785 1595 7190 7 Tigra 13510 7499 6011 4 Fiesta 7310 1050 6260 8 Vectra 18140 6499 11641 4 Fiesta 7875 1495 6380 11 Cosra 8900 4995 3905 2 Escort 9105 2033 6805 7 Nova 5599 1000 4599 10 Escort 12125 4295 7830 3 Cavalier 10150 850 9300 10 Escort 11800 4700 7100 5 Astra 13740 2906 10840 6 Fiesta 8680 3200 5480 4 Corsa 7840 4976 2864 4 Focus
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Gary's Car Sales Mathematics Coursework
1.6 11 5,595 4 Ford 11,000 41,000 1.6 12 4,995 3 Ford 9,880 34,000 1.4 13 5,595 4 Ford 14,000 55,000 1.6 14 4,995 4 Rover 11,500 40,000 1.4 15 2,600 7 Rover 12,000 82,000 1.6 16 1,000 10 Peugeot 6,200 119,000 1.1 17 750 11 Peugeot 5,100 96,000 1.0 18 1,350 8 Ford 9,140 108,000 1.6 19 2,950 8 Ford 17,750 96,000 2.9 20 3,250 7 Vauxhall 9,990 86,000 1.6 21 5,650 3 Vauxhall 11,150 34,000 1.6 22 4,600 2 Rover 7,300 17,000 1.1 23 5,400 1 Rover 7,300 11,000 1.1 24 4,800 1 Rover 7,300 26,000 1.1 25
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A Data Handling Project for Used Car Prices
It will not be appealing to customers not only because of this, but also because of its physical appearance. It may look worn out on the interior and outside and will not have been subject to any modern conveniences, such as air conditioning and other design enhancements. All of these design enhancements would physically improve the used cars appearance, and the value of the car as well. Collecting My Data I obtained the information for my Data Handling Project from the Microsoft Excel spreadsheet, which was provided by school.
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The task for this investigation is to statistically analyse the data given to compare Grays used car sales with the other pieces of information given in the table.
40,000 82,000 119,000 96,000 108,000 96,000 86,000 34,000 17,000 11,000 26,000 51,000 9,000 43,000 142,000 23,000 48,000 26,000 37,000 9,000 13,000 42,000 65,000 1.6 1.1 2.0 2.0 1.2 1.6 1.8 1.7 1.4 1.6 1.6 1.4 1.6 1.4 1.6 1.1 1.0 1.6 2.9 1.6 1.6 1.1 1.1 1.1 2.0 1.8 1.0 2.3 1.3 1.3 1.3 1.3 1.3 1.4 2.0 1.4 Grays Car Sales The task for this investigation is to statistically analyse the data given to compare Grays used car sales with the other pieces of information given in the table.
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Used car prices
* Does the length of a car's MOT affect its value? * If a car has air conditioning, then does its value rise? For this investigation I am going to take a sample size of 60 cars from which I will try and take at least 2 of each car, so that I am able to compare two of the same types of car. However, the sample will not be random if I choose the cars myself. Therefore, to make sure that the sample I choose to use is fair, I will place each number into a hat and pick out 60 numbers.
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