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Counting Cars

Introduction:

An invention which has revolutionised the modern world is certainly the car. Invented in the 19^th century, this machine has had an enormous influence on mankind. Distance could be covered quicker than ever before, but most important of all, without using any muscle power. As a matter of fact, the ancient methods of transportation, such as horse and carriage, were rendered useless and obsolete, and were soon replaced by the more efficient use of motor engines, which used a moderate quantity of fuel and never needed any rest.

As a result, the automotive industry began to develop and expand quickly. Many important car firms, such as Ford and Renault, were already established by the turn of the century. Production began to become faster and faster. The introduction of mass production of automobiles by Henry Ford decreased prices which had originally been only for the rich. Every family could now afford one.

Naturally, with more customers, the firms had to build specific car types in order to satisfy their customers. Consequently, we can now witness a vast variety of vehicles from the smallest and cheapest to the biggest and most expensive.

However, in the last couple of decades scientists have realised that this huge number of cars is having an adverse effect on our world. As a matter of fact, many poisonous gases are emitted by the exhaust pipes of the millions and millions of cars. These gases also contribute to the phenomena of global warming, also know as ‘The Green House Effect’.

Recently, there have been improvements in cutting down the amount of poisonous gases emitted. However, in many countries it is still a critical problem. In Italy, for instance, smog levels are so high that the Government has had to put forward a prevention scheme which bans the use of cars the first Sunday of every month. In some states in the USA, people are forced to ‘pool’ cars, meaning that more than one person has to be travelling in the car so that the vehicle is actually being used to its full extent.

The Investigation:

As I have just mentioned above, ‘car pooling’ would be a very effective way of decreasing the amount of pollution produced. However, for many people, this could become a nuisance. This leads to the investigation which I will carry out. In fact, I will be surveying the number of people in most cars. With the information collected I will be able to decide whether the statement “most cars contain one person” is correct or not.

In order to collect the data, I will go about the streets of Milan counting cars in place for at least half an hour. Naturally, when data is gathered by observation there are a number of different factors which will need to be taken into account:

· Time: People use their cars at different times. It is likely that less people will be driving late at night, than in the morning during rush hour.

· Place: In the centre, there will be a wider use of the car than in the suburbs, since most people work in the city centre.

· Weather: It is likely that people prefer not to use their car on a sunny day and instead walk in order to enjoy the good weather.

· Length of time: The data needs to be gathered over a sufficient time period.

As a result, taking in consideration all of these factors, I have decided to take my results over a seven day period. I will change my location with nearby streets as well as ones in the outskirts in order to have a wider sample. I Additionally, I will note down my observations for at least half an hour and I will try to take down readings on days of different weather, however, I cannot control this environmental factor, and therefore, it may not be possible.

I will record my results in a table, similar to the one shown below. With the results, I will be able to calculate important values such as the median, the mode, the mean and the standard deviation, which are necessary in order for me to achieve a decent conclusion. In addition to this, I will be also drawing various graphs, such as pie- or bar-charts, which will help me further in coming up with a good conclusion.

Date, Time, Place, Weather
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1
2
3
4
5<
			Total	Total

Whilst going around the streets of Milan counting cars, I needed a table in which I could easily record my results. This is the table which I used in order to count the cars.

*Date, Time, Place, Weather*
Cars with 1 person
Cars with 2 people
Cars with 3 people
Cars with 4 people
Cars with 5 or more people

Results:

Wed 16 Feb, 7:30, Piazzale Udine, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	118	118	118	-0.38	0.14	0.14
2	24	142	48	0.62	0.38	0.76
3	4	146	12	1.62	2.62	7.86
4	6	152	24	2.62	6.86	27.44
5<	2	154	10	3.62	13.10	65.5
			Total 212	Total 101.7

Wed 16 Feb, 17:30, Largo Augusto, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	120	120	120	-0.77	0.59	0.59
2	131	251	262	0.23	0.053	0.11
3	25	276	75	1.23	1.51	4.53
4	8	284	32	2.23	4.97	19.88
5<	4	288	20	3.23	10.43	52.15
			Total 509	Total 77.26

Sat 19 Feb, 17:30, Via Oglio, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	27	27	27	-0.67	0.45	0.46
2	15	42	30	0.33	0.11	0.22
3	4	46	12	1.33	1.77	5.31
4	2	48	8	2.33	5.43	9.72
5<	1	49	5	3.33	11.09	55.45
			Total 82	Total 71.16

Sun 20 Feb, 17:30, Largo Augusto, Sunny
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	41	41	41	-1.19	1.42	1.42
2	94	135	188	-0.19	0.036	0.072
3	27	162	81	0.81	0.66	1.98
4	21	183	84	1.81	3.28	13.12
5<	3	186	15	2.81	7.89	39.45
			Total 409	Total 56.04

Mon 21 Feb,23:30, Largo Augusto, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	3	3	3	-1.64	2.69	2.59
2	51	54	102	-0.64	0.41	0.82
3	12	65	36	0.36	0.13	0.39
4	12	77	48	1.36	1.85	7.4
5<	6	83	30	2.36	5.57	27.85
			Total 219	Total 39.05

Tue 22 Feb, 11:30, Largo Augusto, Sunny
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	232	232	232	-0.39	0.15	0.15
2	108	340	216	0.60	0.36	0.72
3	10	350	30	1.60	2.56	7.68
4	3	353	12	2.60	6.76	27.04
5<	1	354	5	3.60	12.96	64.80
			Total 495	Total 100.39

Tue 22 Feb, 17:30, Via Oglio, Sunny
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	52	52	52	-0.42	0.18	0.18
2	13	65	26	0.58	0.34	0.68
3	4	69	12	1.58	2.49	7.47
4	3	72	12	2.58	6.65	26.6
5<	0	72	0	3.58	12.82	64.1
			Total 102	Total 99.03

Wed 23 Feb, 17:30, Via S. Barnaba, Sunny
Number of people in the vehicle x	Frequency F	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	60	60	60	-0.72	0.52	0.52
2	38	98	76	0.28	0.078	0.16
3	12	110	36	1.28	1.64	4.92
4	3	113	12	2.28	5.19	20.76
5<	3	116	15	3.28	10.75	53.75
			Total 199	Total 80.11

Thur 24 Feb, 7:30, Largo Augusto, Sunny
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	243	243	243	-0.46	0.21	0.21
2	114	357	228	0.54	0.29	0.58
3	18	374	54	1.54	2.37	7.11
4	4	378	16	2.54	6.45	25.8
5<	3	381	15	3.54	12.53	37.59
			Total 556	Total 71.29

Thur 24 Feb, 17:30, Via S. Barnaba, Sunny
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	64	64	64	-0.67	0.44	0.44
2	42	106	84	0.33	0.11	0.22
3	10	116	30	1.33	1.77	5.31
4	4	120	16	2.33	5.43	21.72
5<	2	122	10	3.33	11.09	55.45
			Total 204	Total 83.14

Fri 25 Feb, 17:30, Piazza S. Babila, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	229	229	229	-0.53	0.28	0.28
2	142	371	284	0.47	0.22	0.44
3	23	394	69	1.47	2.16	6.48
4	2	396	8	2.47	6.10	24.40
5<	4	400	20	3.47	12.04	60.20
			Total 610	Total 91.8

Sat 26 Feb, 7:30, Largo Augusto, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	28	28	28	-0.85	0.72	0.72
2	50	78	100	0.15	0.023	0.046
3	8	86	24	1.15	1.32	3.96
4	2	88	8	2.15	4.62	17.85
5<	1	89	5	3.15	9.92	49.6
			Total 165	Total 72.18

Sat 26 Feb, 17:30, Via S. Barnaba, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	19	19	19	-1.06	1.12	1.12
2	36	52	72	-0.06	0.0036	0.0072
3	5	57	15	0.94	0.88	2.64
4	3	60	12	1.94	3.76	15.04
5<	2	62	10	2.94	8.64	43.20
			Total 128	Total 62.01

Sat 26 Feb, 22:30, Largo Augusto, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	12	12	12	-1.53	2.34	2.34
2	42	54	84	-0.53	0.28	0.56
3	24	78	72	0.47	0.22	0.66
4	15	93	60	1.47	2.16	8.64
5<	3	96	15	2.47	6.10	30.50
			Total 243	Total 42.7

Sun 27 Feb, 7:30, Piazzale Udine, Cloudy
Number of people in the vehicle x	Frequency f	Cumulative Frequency	xf	(x – x)	(x – x)²	(x – x)²f
1	35	35	35	-0.71	0.50	0.50
2	27	62	54	0.29	0.084	0.17
3	3	65	9	1.29	1.66	4.98
4	3	68	12	2.29	5.24	20.96
5<	2	70	10	3.29	10.82	54.10
			Total 120	Total 80.71

Conclusion:

After I had collected the data, I began calculating some averages and figures of spread and straight away I saw that there were some influential factors which changed the sample from day to day. In fact, in most cases, I found that the mode was 1, since it usually had the largest group. However, if we look at the results taken at night or during the week-end, we see that the modal value is 2. A similar pattern is also seen in the median.

The mean, on the other hand, showed us some interesting values. As a matter of fact, the value was never less than 1 or more than 3. In most cases it was in between 1.5 and 2.0, with some rare peaks at 2.53 or 2.64. This suggests that most cars have either 1 or 2 people. Just like the median and the modal values, also the mean has a similar pattern: we find the lowest values during the working week, while we find the highest numbers during the week-end or the evening.

If we look at the spread of the data, we can again see some interesting facts. First of all, we see that the range was almost always the same: 4. This is due to the fact that there are few cars which can carry more than 5 people, however, I did notice the rare occurrence of some cars containing seven or more people. Naturally, such events should not occur since they are prohibited by the law and are extremely dangerous.

A similar pattern was also seen in the inter-quartile range. In fact, apart from the first group of results, every other group has an inter-quartile range of 1. This value was calculated by subtracting the lower quartile from the upper quartile, which were most of the time 2 and 1, respectively. This therefore means that half of the data lies in this range, once again showing that most cars carry 1 or 2 people. Nevertheless, there were a couple of times when the lower and upper quartile values were 2 and 3, thus suggesting that most of the cars carried either 2 or 3 people, however, these values came from the group of results taken either during the evening or during the week-end.

Finally, the standard deviation was usually between 0.5 and 1.2, reaching its peak at 1.21. This consequently suggests that there is not a very large spread. That is, if the mean is 1, the number of people in the car will be either 1 or 2, with a slight majority towards the former.

Therefore, in conclusion, I partly agree with the statement ‘most cars contain one person’. Most of the time this is true, especially during the working week. However, at night and throughout the week-ends, there is strong evidence to suggest that there is a tendency of cars containing 2 people, if not more. This can be due to multiple factors. Probably during the working week, people go to or return from work by themselves. During the evening and in the week-ends, however, family and friends probably get together in order to socialise and consequently there is a strong tendency to travel together, in one car. Last, but not least, I would also like to point out the enormous difference between traffic on main streets and side streets. As a matter of fact, I would count about 40 cars in a side street, when just 50 metres away, on the main road, I would count about 400 cars.

The only major problem which I encountered whilst carrying out this investigation was that on some occasions I realised that I was counting the same car over and over again, since it kept on travelling in circles, probably because it couldn’t find a parking place. Anyhow, this affected my results, even though I don’t think by that much since I did collect a big sample in order to make it as reliable as possible. A way to solve this problem could be to take down the car’s number plate in order to be sure that you are not counting the same car twice.

Some possible further investigations could concern the majority of sex on the vehicle or the age of passengers. This could help in seeing whether cars are used by the whole population or just by certain groups. This, however, would be more complicated and need more involvement than just counting the cars, since you would have to ask the people for their age, since some people may look older or younger than they actually are.