Statistical Modelling for Public Transport Infrastructure Planning

STATISTICAL MODELLING
STUDENT ID:
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Section 1: Introduction
a) In cities, a crucial challenge for planners is to ensure that the transport infrastructure must be
robust to cater to the ever increasing population while ensuring efficiency and also affordability
that is associated with public transport system. For enabling the same, the relevant authority
tends to make changes in route of timetable and stoppages so that the available infrastructure
can be utilised more efficiently and serve greater number of people. In this regards, some of the
people may be negatively impacted but the larger good is considered more important. As a
result, the decision to change timetable and stoppages must be taken after due research from
specialised agencies who understand the preferences and the issues faced by the travellers
(Meyers, 2017).
b) In order to determine whether the given dataset is primary or not, it needs to be seen if the
underlying data has been collected by the entity conducting the research. It is apparent that the
given data in dataset 1 has neither been collected by myself nor has been collected by the
university. This data was computed by an external agency and hence the given dataset 1 would
be termed as secondary data (Eriksson and Kovalainen, 2015). The given dataset has an
underlying sample size of 1000 observations and the given information is represented in the form
of six variables. For the variables such as location, tap, mode the underlying data type is
categorical and since automatic arrangements of the respective values is not possible; hence the
applicable measurement scale is nominal. On the other hand, date is also a categorical variable
but the underlying measurement type of ordinal since arrangement in an orderly manner without
any additional information is possible. Count and time are both quantitative variables, however
the relevant measurement scale for the former would be ratio while for the latter would be
interval (Flick, 2015). The cases in the dataset would correspond to a tap on or tap off at a given
location at a given time through a defined mode on a particular date. The frequency of each of
these cases is represented using the count variable.
c) The dataset 2 is a primary data since it has been obtained from any source but rather has been
collected through the use of survey (Hair et. al., 2015).. The focus of the survey was only on
recording two variables namely the preferred mode of public transport coupled with the underlying
gender of the respondent. Even though dataset 2 is primary data unlike dataset 1, but this would
not automatically imply that the former is more accurate than the latter. For the reliability of data
obtained from primary source, the sample needs to representative of the underlying population.
This is clearly not the case because of the following two reasons (Eriksson and Kovalainen, 2015).
 The sample size is only 30 which is very small compared the population and the key
attributes driving the preferences.
 Random sampling is not deployed and instead the sample selection has been done based on
convenience.
In the given case, the two variables i.e. transport mode and gender are variables of categorical form
with a nominal measurement scale (Hillier, 2016).
Section 2: Single variable Analysis – Dataset 1
a) The usage of public transport numerical summary for the given sample data is as shown below.

The graphical illustration of the above information is as given below.
As per the given summary table and graph regarding the transport mode, it is apparent that the
mode which is most frequently used is train as is clear from the sample data where it has the
maximum frequency. However, bus mode is also quite close and trails by only a minimal insignificant
difference. But the contribution of other means of transport besides bus and train is only 5% thereby
indicating a high degree of reliance on bus and train in the public transport system. As a result, going
forward it is desired that relevant measures must be undertaken to strengthen the bus and train
infrastructure so that it can handle higher number of passengers. Alternatively, the other means of
public transport should be explored so as to ease the pressure and underlying traffic on bus and
train.
b) The first step in the hypothesis test is to define the relevant hypotheses which is carried out
below.
The level of significance for the test is defined as 0.05.