Analyzing NSW Transport System Data To Improve Public Transport

Dataset Description

The movement of goods and services from one place to another to create any kind of utility is what we call transport. Can you imagine a world without transport? Where people, goods and services cannot move from one place to another? It would be a totally dead world. The nerve center of any economy is transport. It facilitates other factors of production such as labor and raw materials (Dey & Teesta 2010) and (Halder 2012). Transport makes sure that human labor is at the production place at the required time so that form utility can be created in the raw material. It also ensures that the raw material is at the required location at any particular time. The above has made transport to have a strong positive correlation with the growth of the economy (Rogerson & Peter 2010). There are various modes of transport and different means of transport. We have road, rail, water and air as means of transport. We also have various modes of transport such as by bus, rail and ferry just to mention but a few. It is argued that a country with proper transport network always experience significant economic group (Badhuri 2013) and (Munshi & Sunil 2010).

In the international journal of economic research, Professor Bilal puts it that however much effort can be put to utilize the natural resources of a country; one hundred percent result cannot be achieved without transport facilitation. He adds that the fast development of the economy needs good transport network. He links poor economies to poor transport network. According to him, countries that are doing well economically have better roads, railways, ports and airways. Lastly, he says that the cost of economic growth of a nation will depend on the type of transport network of that particular nation.

In order to be able to answer various questions related to transport asked by the government of New South Wales, two types of datasets were collected. Both the data contained transport information. The first dataset had five variables. Some were numerical variables while some were categorical variable. The variables were location, mode of transport, count and tap. The categorical variables in this case were location, mode of transport and tap. The only numerical variable involved here was the count. Location means the station or terminus where the mode of transport stops to pick and to drop passengers. Mode is the vessel that carries the goods and passengers. Count refers to the number of passengers travelling on a particular mode.

The other data had only two variables. These were gender and mode of transport that was used by each individual. So the variables are categorical (gender) and numerical (count). The data is primary data since the method that was employed to collect this data was survey.

Just like any research, this research had two main objectives which it was pursuing.

• To establish the mode of transport that was majorly used by majority of the travellers in the city of New South Wales between the dates 8^thand 14^th of August, 2014.
• To find out if there was any mode of transport that is used by in New South Wales that uses more than 50% of the people.

• Is the tap on and off mean counts equal?
• Do males and females have difference in preference when it comes to mode of transport?

Hypothesis 1

H₀: The mean count of tap off is equal to the mean count of tap on.

Versus

H₁: The mean count of tap off is significantly different to the mean count of tap on.

Main Objectives of Research

Hypothesis 2

H₀: The preference of males and females do not differ about the choice of transport mode.

Versus

H₁: The preference of males and females differ significantly about the choice of transport mode. 

1. Transport mode frequently used.

Table 1

Figure 1

The graph and table above represents how people travelled in New South Wales according to mode of transport. 479 passengers used bus as a mode of transport. This number accounted for 47.9% of the total. 453 passengers used bus as a mode of transport. This number accounted for 45.9% of the total. 37 passengers used ferry as a mode of transport. This number accounted for 37% of the total. 37 passengers used light rail as a mode of transport. This number accounted for 31% of the total. It therefore follows from the results majority of the people in New South Wales travel by bus. The government should therefore concentrate more in improving travelling by bus.

1. Is there more than 50% usage of modes of transport by public?

Hypothesis

H₀: There is no mode of transport that is used by more than 50% of the public.  

Versus

H₁: There is a mode of transport that is used by more than 50% of the public.

Table 2

The research findings on table 2 indicate that the highest proportion that has been used of a particular mode of transport is 47.9%. This is a clear testimony that there is no single mode of transport that has served more than 50% of people. The highest percentage was 47.9%.

1. Tabulation  for location and count

Table 3

Figure 2

The pie chart above is a representation of the number of people that are being served by the railway line from the three destinations to central (Parramatta, Bankstown and Gosford). The number that travelled from Parramata station to central constituted to 35%. Those who travelled from Bankstown to Central constituted to 37% while those passengers that travelled from Gosford station to Central was 28%. Comparing the three stations, the government of New South Wales should consider building the railway tunnel from Bankstown town to central since this is the line that seems to be used by many passengers.

1. Hypothesis test

Hypothesis

H₀: The mean count of tap off is equal to the mean count of tap on.

Versus

H₁: The mean count of tap off is significantly different to the mean count of tap on. 

Results

Table 4

The table above is of results of a t-test conducted to establish whether the mean count of tap off is significantly different to the mean count of tap on or otherwise. The p-value calculated was 0.07 while the level of significance is 0.05. Because the p-value computed is greater than the level of significance (0.05), the null hypothesis is not rejected thereby making a conclusion that the mean count of tap off is equal to the mean count of tap on.

1. Since the mean count of tap off is equal to the mean count of tap on, this enables the government to look for others measurement in order to decide whether to continue with the plan of building the underground tunnel or not

1. Hypothesis test

H₀: The preference of males and females do not differ about the choice of transport mode.

Versus

H₁: The preference of males and females differ significantly about the choice of transport mode. 

Results

Table 5

The table above is of results of a t-test conducted to establish whether the mean count of tap off is significantly different to the mean count of tap on or otherwise. The p-value calculated was 0.46 while the level of significance is 0.05. Because the p-value computed is greater than the level of significance (0.05), the null hypothesis is not rejected thereby making a conclusion that the preference of males and females do not differ about the choice of transport mode.

1. Mode preference by gender

Research Questions

Figure 3

The figure above shows the distribution of the two genders by the mode of transport that they like. It can be seen that 17 female and 20 males preferred travelling by bus. Under ferry, the males and females preferred it in equal measure. 32 females and 28 males preferred travelling by light rail. 19 females and 20 males preferred travelling by light rail.

The analysis of transport data brought various things to limelight. For example, it was found that government can only build an underground railway line between Bankstown and Central. This is so considering that this route has got many passengers. This will also ensure that the government invests wisely and in projects that will bring back revenue. The research also discovered that 479 passengers used bus as a mode of transport. This number accounted for 47.9% of the total. 453 passengers used bus as a mode of transport. This number accounted for 45.9% of the total. 37 passengers used ferry as a mode of transport. This number accounted for 37% of the total. 37 passengers used light rail as a mode of transport. This number accounted for 31% of the total. It therefore follows from the results majority of the people in New South Wales travel by bus. To add on, the highest proportion that has been used of a particular mode of transport is 47.9%. This is a clear testimony that there is no single mode of transport that has served more than 50% of people. The highest percentage was 47.9%. Analyzing the choice of the two by the mode of transport that they liked, it was found that 17 female and 20 males preferred travelling by bus. Under ferry, the males and females preferred it in equal measure. 32 females and 28 males preferred travelling by light rail. 19 females and 20 males preferred travelling by light rail. It was also found that the preference of males and females do not differ about the choice of transport mode. The research also sought to establish whether the mean count of tap off is significantly different to the mean count of tap on or otherwise. The p-value calculated was 0.07 while the level of significance is 0.05. Because the p-value computed is greater than the level of significance (0.05), the null hypothesis is not rejected thereby making a conclusion that the mean count of tap off is equal to the mean count of tap on. The number of people that travel from Parramata station to central constituted to 35%. Those who travelled from Bankstown to Central constituted to 37% while those passengers that travelled from Gosford station to Central was 28%. Comparing the three stations, the government of New South Wales should consider building the railway tunnel from Bankstown town to central since this is the line that seems to be used by many passengers.

References

Dey, Teesta, R. 2010. “Sub-urban Railway Network of Kolkata A Geographical Analysis”, Sarkar, Ashis (ed.), E-Traverse, Indian Journal of Spatial Science, vol. III no. 3

Halder, D. K. ed. 2012. “Urban Transport Pricing and Planning”, Allied Publishers Limited, Kolkata.

Rogerson, Peter, A. 2010. “Statistical Methods for Geography, A Student’s Guide”, SAGE Publications Ltd., London

Bhaduri, 2013. “Mass Transport Services in Calcutta Metropolitan Area”, Vaidya, B.C. (ed.), Geography of Transport Development of India, Concept Publishing Company. New Delhi.

Munshi, Sunil, K. 2010. Geography of Transportation in Eastern India under the British Raj, Calcutta

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