Analysis of Public Transport System in NSW using Opal Tap On/Off Data

Table of Contents
Executive summary:................................................................................................................................2
Section 1: Introduction...........................................................................................................................2
Section 2: Analysis of single variable in Dataset 1.................................................................................3
Section 3: Analysis of two variables in Dataset 1...................................................................................5
Section 4: Collect and analysis Dataset2:...............................................................................................7
Section 5: Discussion & Conclusion........................................................................................................8
References:..............................................................................................................................................9

Executive summary:
The analysis based on data of opal tap on and tap off location between 8th to 14th August 2016 in
Australia and to provide recommendations for public transport system.
According to the analysis of the sample data, the employees was using buses 46.3% and trains 50.30% as
a choice of public transport. There are 50% of public transport users in NSW use the train mode of
transport.
Parramatta station have mostly used tap on/off location, so government can build underground railway
station from Parramatta station to central. Also, NSW government can build underground railway
station from Parramatta station to central.
Section 1: Introduction
a. The article based on the analysis of public transport system. The data for the study has been provided
by transport for NSW, the provided data is a subset of opal tap on and tap off location between 8th to
14th August 2016 in Australia.
Consider the article “Transport systems and their impact con gender equity”,
(https://www.sciencedirect.com/science/article/pii/S2352146517305355), the analysis shows that there
are variances in transport convenience between men and women, and women have less accessibility
because of the higher travel times and percentage of income spent in transport. In the higher income
regions, men and women mark comparable number of journeys per day and spend comparable
percentages of their income. Also, it was exciting to see that, women chose cheapest mode, and at
whatever time possible, women preferred the private vehicle like car or taxi among the public transport
modes.
The requirement of the study is to provide the recommendations to improve public transport system.
So, business question can be assume as, is there a significance difference between the proportions of
particular mode of transport.
b. The data collection can be divided into two types, the first one is Primary data, which collected
directly from the employees on the basis of designed questionnaire. The other one is Secondary data,
which collected from some other resources according to the requirement of analysis. (Goodwin, 2012).
The dataset 1 has been provided by transport for NSW, it is a subset of opal tap on and tap off location
between 8th to 14th August 2016 in Australia. Thus, dataset 1 is collected by other source. Hence, it is a
secondary data.
The collected data can be further categorized as qualitative or quantitative measurements, the
qualitative data contains the values for the ordinal level and the nominal level of measurements.
And, the quantitative data contain the values of interval or ratio level measurements. (Morgan, 2013).
The dataset-1 contains data of 1000 peoples which have 5 variables that are as follows:

1. Mode type of public transport which are Bus, Train, Ferry and Light Rail indicated by the variable
mode. The variable mode has divided into four categories, so it is a nominal level variable.
2. Date of tap on/off held which is date, the variable date indicates the time when the tap on/off happed
by the passenger. It contains the continuous values, so it is an interval level of measurement.
3. The tap on/off which is tap have two attributes as tap on/off, so it is a nominal level variable.
4. Time of tap on/off held which is time, the variable time indicates the time when the tap on/off
happed by the passenger. It contains the continuous values, so it is an interval level of measurement.
5. locations of spots which is “loc” indicates the location of tap on/off.
6. Count, the variable count indicates the number of tap on/off at the particular location and time. The
variable count contains, the numeric values, so it is an interval level of measurement.
c. The dataset-2 collected by offline survey, I asked questions to employed people about their transport
type, tap on/off and gender type. Thus, it is directly collected from the working people, thus dataset 2 is
a primary data.
The dataset2 is collected by 40 working people, which is greater than sample size 30. Thus, the results
obtained from the study will not be biased. The variable mode indicated the type of public transport
which are Bus, Train, Ferry and Light Rail indicated by the variable mode. The variable mode has divided
into four categories, so it will be nominal level variable.
The variable tap specifies the tap type which has divided into 2 categories (on and off), so it is a nominal
level variable. The variable gender specifies the type of gender which has divided into 2 categories (male
or female), so it is a nominal level variable.
Section 2: Analysis of single variable in Dataset 1
a. The numerical for the type of public transport is shown below:
Row Labels Count of mode Percentage of mode
bus 463 46.30%
ferry 19 1.90%
lightrail 15 1.50%
train 503 50.30%
Grand Total 1000
According to the above numerical summary, out of 1000 times, buses was used 463 times, trains was
used 503 times, ferry was used 19 times and lightrail was used 15. The people mostly prefer the train
(50.30%) and the bus (46.30%) for the public transport. Thus, train was most used by the NSW people
during 8th to 14th of August 2016.