# STATISTICAL ANALYSIS FOR NEW SOUTH WALES TRANSPORT SYSTEM

Document Type:Research Paper

Subject Area:Statistics

Also the common statistical tests such as chi-square test of independence, two- paired sample t-test and hypothesis testing in one population for proportion were used that lead to the correct interpretation of the statistical data (ANDERSON, 2017). Introduction This report summarizes the collecting and analyzing of statistical data of the NSW transport system to mainly find out which type of public transport is preferred by the most users. The purpose of these report is to document all models and techniques used during the statistical analysis that leads to a better conclusion and interpretations (Johnson & Kuby, 2012). A data analysis was conducted on the mode of transport variable against the date variable to determine which type of transport was mostly used between 8th to 14th August 2016 using bar charts and tables. A paired sample t-test was performed to find out whether there is a difference between the mean counts of taps on and off. In addition hypothesis testing for one population was also tackled to investigate if there was more than 50% of public transporters users in NSW Government used a certain type of transport. Lastly, a chi-square test was performed on the surveyed data to determine whether there is a difference in gender in terms of their mode of transport that they use (Johnson & Kuby, 2012). The Dataset 1 comprises 1000 observations and 6 variables (Transport for NSW, 2017). The 6 variables are mode, date, time, loc, tap and count. The variables are both qualitative and quantitative categories. For qualitative category, we have nominal data that encompasses the tap variable.

Nominal data refers to the data where the order is meaningless hence this variable cannot be transformed to a numerical value. Date and counts variables fall under quantitative category hence data can be transformed into numeric value. Dataset 1 is secondary data because its data that is collected from an existed online library or source (Transport for NSW, 2017). Dataset 2 is primary data. This data was obtained directly from an online research survey. The research is unbiased since all the gender variable observations were used is almost the same. Obtaining the data was very tedious from the online survey research sites. This is because creating Google forms and spreadsheets took some time to create and very cumbersome. The dataset contains 400 observations and 2 variables. The third public mode of transport used by NSW Government is Ferry with 1718 people using it.

The lastly used is LightRail with 861 people using it as a public transport mode. Table 2. shows a table of the total of people using different modes of public transport in NSW during 8th and 14th August 2016 and their percentages. Figure 2. Alpha (α) = 0. Sample proportion of number sampled (p0) = 0. Decision Rule Reject H0 if Z > 1. Findings Z calculated was 74. Conclusion In conclusion, the null hypothesis is rejected. shows the total number of taps on and off in each of the three stations train only. Figure 3. shows the Column chart for the total sum of counts on the three stations. Conclusion From the above displays, it clearly shows that Paramatta station had the highest number of people using the train as their means of public transport in NSW Government. Bankstown and Gosford had slightly fewer people using the train as the type of transport as compared to Paramatta station.

In conclusion, the null hypothesis is rejected. Therefore, there is a difference between the mean of taps on and off at 5% level of significance. Recommendation c. The NSW Government should construct an underground Railway line from Paramatta to the central station. This is to reduce the traffic that is caused in this station has it has a lot of people operating in it i. Bar charts The clustered column bar chart was used to give the visual impression of the graph about the test of preference between different genders and their mode of transport that they like in NSW Government. Findings All the genders tend to like the same mode of transport with no big margin in them. In figure 4. above it also clearly shows that both the males and females prefer the train to other modes of transport.

According to the research, a great number of both the genders also consider using the bus as their mode of transport. Reject H0 if chi- stat > chi- tables Findings The chi- stat was 2. and the chi-tables was also found to be 7. Hence Chi-stat < Chi-tables. Conclusion In conclusion, we fail to reject the null hypothesis. Therefore we conclude that there is no significant difference in preference between the different genders in terms of their mode of transport. The two datasets unbiased were easy to work with that led to the valid and genuine discussions. This was due to the fact there was no omission of data in all the variables in the two datasets. The NSW Government should put more emphasis on train type of public transport as more people use it in travelling around the city.

The future research should be done on the time variable against the mode of public transport. This is to determine which type of public transport is most used during the morning hours, afternoon and even in the evenings. Opal Tap On and Tap Off. Retrieved from Opal Tap on and Tap Off Location - 8th to 14th August 2016.

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