- Tax
I believe that tax is influential figure on some cars but not all of them. If the car is very old and has high tax the car price will still be low regardless if the car has high tax. Tax is important for some cars and mostly that as the tax increases the car price will increase but if the car has low tax the car price will decreases. Overall tax will play an important role in some cases and therefore the graph will not have strong correlation.
I will be investigating whether the price could be dropped by some factors such as mileage and age.
My first comparison is between Engine size and prices. The graph below shows the result of my comparison.
The graph above demonstrates that as the engine size increases, the car price increases as well. The relationship in this graph is a strong positive correlation graph because the car price increases as engine size increases. This graph explains that engine size has influence on second hand car prices.
The result that has been circled is slightly different and unexpected. As you know the car price increase if the engine size increase, but in the circled result the engine size is low but the price is high.
The car is Mercedes make, which, is highly rated between the customers and has other factors, which increased the price such as The car is only one year used which shows the car is still in good condition, also has 5 doors, red colour which is very attractive and been used by one person which demonstrate the car in good condition.
Cumulative frequency will help me to gather an accurate result for the median, lower and upper value and also the inter quartile range. Cumulative frequency will help me to decide if the factor affected the car price. This means that cumulative frequency is essential to gather an accurate result and gain more evidence. Cumulative frequency is used to determine the number of observations that lie above (or below) a particular value in a data set. The cumulative frequency is calculated using a frequency distribution table, which can be gathered from stem and leaf plots or directly from the data.
HERE IS CUMULATIVE FREQUENCY FOR THE ENGINE SIZE 1.4
Median
Median=Total +1 ÷ 2
11+1÷2
12÷2=6
so median =0
INTER QUARTILE
Inter quartile range = upper value – Lower value
Upper value=Total +1 × ¾
11+1 × ¾
=12 × 3/4
= 9 upper value=1
Lower value=total + 1 × ¼
11+1 × ¼
=12 × ¼
=3 lower value=0
Interquartile range =1 - 0= 1
Here is another cumulative frequency table for the engine size 1.6
- Median
Median=Total +1 ÷ 2
9+1 ÷ 2
10 ÷2 = 5
INTER QUARTILE
Inter quartile range = upper value – Lower value
-
Upper value= Total +1 × ¾
= 9+1 × ¾
= 10 × ¾
= 7.5 upper value=2
-
Lower value= total + 1 × ¼
9+1 × ¼
=10 × ¼
=2.5 Lower value=0
Inter quartile range=2 - 0 =2
My third table is for the engine size 1.8. As my database contains 48 cars I find it difficult to have another widely spread engine like 1.4 and therefore I decided to use 1.8.
- Median
Median=Total +1 ÷ 2
5+1 ÷ 2
6 ÷2 = 3
INTER QUARTILE
Inter quartile range = upper value – Lower value
Upper value= Total+1 × ¾
= 5+1 × ¾
= 6 × ¾
= 4.5 upper value=2
Lower value= total + 1 × ¼
5+1 × ¼
=6 × ¼
=1.5 Lower value=1
Inter quartile = Upper value – lower quartile
2 – 1= 1
My second comparison is between age and prices. In order to find out what effect has age on second hand car prices I have decide to use graphs to compare them. I have chosen scatter graph for this comparison.
The graph below shows the result of my comparison.
The result above shows, as the age of the car increases the price decrease. This graph is a negative correlation graph because the car price decreases. The result above shows that age has influence on second hand car prices and age is considered as a key factor when you purchase it. The result which been circled is different from other results. The method for this comparison is as the age increases the price decrease but in this result that price hasn’t dropped much because of other factors, which could affected the price, such as number of doors, colour, mileages and the make. This car has been used for only 14000 miles which is not very long comparing to the other cars also the car has bright and attractive colour also 5 doors which is suitable for most of the people and finally the make is Mercedes which is very popular car.
My third comparison is between mileage and second hand car price. This comparison will look at what effect that mileage has on second hand car price. The mileage is another vital factor and has huge affection on second hand car prices.
This below graph shows the role of mileage.
As you see the graph above reveal that as the mileage increases the car price decrease. The graph is a negative correlation graph because the car price decreases. The graph shows that mileage has affection on second hand car price. There is circled result, which is quite different, than others. The result has other factors, which caused this result such as number of door, colour, age and make.
This car is a Mercedes car, which been used only for 1 year also this car is a red colours and it’s very attractive. The price hasn’t dropped because of the good condition and the good features.
This is the fourth comparison, which I have decided to be between Tax (month) and car prices. The tax will have effect on price in two ways. The first way is if the tax is high the price will increase and people will be keener to buy it then others but if it was low the car price could drop and people might not find it suitable or attractive.
The result has showed that tax has a weak affect on second hand car prices. Mainly result above reveal as the Tax increases the second hand car increases as well. The result explains that tax has a weak effect on second hand car prices. The tax plays an important role for some of the car prices, which could effect customer’s opinion and could attract them or prevent them from purchasing the car. The graph is a weak positive correlation graph because the second hand car increases as shown in the graph.
The circled result is different then others and unusual.
As you know if the tax increases the price increases as well but in this result it’s different. The circled result has a high tax but has low price this happened because of other factors, which affected the Price.
The following points explain why the result is unexpected.
- Age
The car has been used for 9 years, which is very long, and reveals the car is not in very good conditions.
- Make
Nissan micra are very old cars. Despite the car is old, Nissan is not a popular car and has less technological features and not fashionable comparing to the other cars.
- Engine size
The engine size for this car is very low. The engine size is only 1.1, which is very poor. In our modern life the engine size is very important because its show the quality of the car.
- Number of doors
This car has 3 doors, which is not suitable for the majority of the customers especially the big families. This will drop the price and become less attractive.
My fifth comparison is between insurance group and second hand car prices. I have decided to compare them in order to find out if insurance has affection on second hand car prices.
The graph below explains the affection.
As you see the graph shows as the insurance group increases the price increase as well. The graph shows that insurance group has an affect on second hand car price. This graph is a positive because the second hand car price increase. As you know the graph is shown that insurance has vital role in the second hand car price and could increase or decrease the price.
The circled result is unpredicted and unusual. As the insurance increases the price increase as well and if the insurance low the price should dropped but in this result the insurance is low but the price still high. The unusual result has been caused because of other factors, which affected the result such as make, age, colour, number of door and mileages. The car has been used for 1 year, the make is Mercedes, which is very popular car and red colour, which is very attractive, and also the car has 5 doors, which is very suitable for most of the people. This shows the car is very good from all areas and explains the result.
The cumulative frequency is calculated by adding each frequency from a frequency distribution table to the sum of its predecessors. The last value will always be equal to the total for all observations, since all frequencies will already have been added to the previous total.
The information contained in the database could be transformed to a frequency table. When the information transformed it will be easier to use, easy to compare and also it will be easier to find the average, median, inter quartile range.
Mode is the most common number
Mode =0
Median= 48+1 divide by 2
=24.5
Median= 1
Conclusion
This coursework was extremely important because it help me to improve in some areas. The coursework improved my ability in using Microsoft Excel because I did not use Excel very often. As my coursework based on database I had to learn some skills, which will be important, and helpful at later stages.
Another advantage I learned is to describe the relationship in the graph more accurately. In numerous occasions I used to say if the graph is positive or weak correlation but now I know how to describe the graphs more accurately by saying if the graph has strong or weak correlation in great details.
Another crucial advantage is box plots. As I had to produce in easier way to show my medium, upper and lower value I have chosen box plots which was unfamiliar to me so I had to learn this method in order to use it in my coursework.
My table forced to obtain number of cars from my data to the table, which was hard because I had huge data, and to gain accurate number of cars I had to count number of cars and repeat it in order to gain an accurate result. This is the main disadvantage in my coursework.
In my investigation I have found that the age affects the second hand price the most since the correlation was strong and there were fewer outliers in the scatter graphs. This is followed by mileage as identical correlations were found and fewer outliers. The least most influential factor to the second hand price of the cars will be the engine size, as it had the most outliers and the graph correlations were not the same for each car make. This means that my hypothesis was incorrect because the mileage follows the age.
If I had additional time I would have used standard deviation which measure the spread and results are more reliable. I also would have proved using coefficient of covariance that age is the factor that affects the second hand price the most. Coefficient of covariance or r gives a value which can terminate which factor is most important. If r = +1, this indicates the correlation is positive. If the value of r is close to +1 then that means the correlation is stronger that the value that is away from +1. The same thing is with -1 which indicates that the correlation is negative. So the closer the value of r is to -1, the stronger the negative correlation. I would’ve used this method to find the values of r for mileage, age and engine size for all four makes. This would have proved which factor influences the second hand price of a car the most.
If I had used more data for this investigation, then the results would have been more concise and reliable. Also, the gradients of the scatter graphs would have been clearer and so would the box plots.
