Analysis of Transport System in Sydney City, NSW

Statistics and Data Analysis
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1. Introduction
a. The transport system in Sydney city in New South Wales is availed through an extensive
operating mode which compose of suburban rail, buses, ferries as well as light rail. The
structure will also be composed of rail transit with the new Sydney Metro opening in early
2019 to form part of this. Based on the 2006 census Sydney city had the highest rate of
public transport usage out of all the capital cities in Australia. The city had up to 80% of its
weekday transport from /to the central city being made via the public transport. This makes
Sydney to be among the Australian’s largest public transport network. The transport system
is structures as explained below;
Road; New South Wales road infrastructure is under the command of the Roads and
Maritime Services (RMS). This body is concerned with driver licensing as well as registration
of vehicles. RMS is involved with direct management of the state roads and avails funding to
the local council roads for purpose of developing the regional roads. With an assistance from
the Federal Government RMS is also mandated by the management of the national highway
system.
In this report the focus will be to analyse the data from the NSW with a focus of making
recommendations on how to improve the public transport system. The task makes use of a
number of research questions to assist breakdown the transport system and assist identify
the limitations.
b. The data set 1 availed is a primary data. This is because it avails primary viewpoint of the
participants as at the given time. When the variables are scrutinised, it can be deduced that
they are a direct response from the participants prior to a breakdown by the researcher.
The data is composed of the modes of transport, location, tap on or off as well as the count
that indicate the total number of tap on/off on a location at a certain date.
The data set 2 was collected from interviewing participants and provision of questions in
some cases. The respondents to be interviewed were randomly selected from streets of
Sydney city. The major challenge faced when collecting the data was lack of adequate
resources Abd time. This limited the sample size to a value which may not represent the
actual situation of the population appropriately.
The data set majorly considered the mode of transport preferred by the different gender set.
The respondents were mainly asked to select between the four options that is bus, train,
light rail and ferry which mode they prefer to use. Each respondent was only allowed to
select one option which he/she will opt to use if presented by all the four alternatives.
1. Analysis of single variable dataset 1
a. The table below gives a summary of the modes of transport used by the NSW occupants.
Row Labels
Sum of
count
Bus 97094
Ferry 3909
light rail 1750
Train 53552
Grand Total 156305

When this data is visually presented using a pie chart, it can be observed that;
The use of bus service was the most popular mode of transport by the occupants of
NSW. 62% of the respondents interviewed admitted to be comfortable with the use of
buses. This was followed by a 34% which preferred using trains. The other modes of
transport which includes ferry, and light rail were only preferred by 1 % of the
respondents.
62%
3%1%
34%
Total
bus
ferry
lightrail
train
To determine ways of improving the transport system in NSW it is thus necessary to
expand the road transport sector as it mostly accommodates the transport needs of the
majority of the population.
b. In the analysis above we have identified that 62% of the respondents make use of buses
as a preferred mode of transport.
To ascertain this case, we wish to verify the hypothesis that 50% of the population
prefer the use of bus as a mode of transport.
So, will begin by first setting up the hypothesis
H0 : x=50 %
H1 ; x >50 %
The parameter x is used to represent the sample population that prefer to use buses.
From here we set up the data in excel and using the data analysis tool conduct a one
tailed hypothesis test.
The result of the analysis is highlighted in the table below
Point
Sum of
count Rank Percent
1 97094 1
100.00
%
4 53552 2 66.60%
2 3909 3 33.30%
3 1750 4 0.00%