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Introduction of How Long Are Bicycles Hired For (On Average) On The Santander London Bicycle Hire Scheme? Assignment
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A) Organizing and Carrying Out the Research
The santander bicycle hire scheme is an eminent programme for travellers to travel around the city, with around 800 docking stations and a facility of availing of bikes rides with over 12000 bikes.
The approach and processes involved in organising and carrying out a research project could be through building up of strategies that could be elaborated as ,
1) Collection and foregathering of resources such as scholar articles, bibliographies, and online sources and building up interactions with them for analysing the london bicycle hire scheme.
2) Pragmatic methods such as surveys, interviews, field work and questionnaires could be used for gaining knowledge and understanding about the people who have already availed the scheme (twp.duke.edu, 2020).
3)development of a working thesis statement backed by sufficient evidence according to the data set and usage of statistical tools and techniques for evaluation and calculating the hiring frequency, number of regular ,irregular and new users availing the facility ,( tfl.gov.uk, 2019).
B) Estimation of Average Length of Bike Hire and Proportion of Bike Journeys Taking Place from or To the “Queen Marys, Mile End” Docking Station.
1) Average Length of Bike Hire
The actual availability of bike services during the week of 2nd week of June starting from 9th june 2021 has been considered and comment can be made on the average length of hire during the period related to the provided dataset. it can be deduced that the average duration spent by bikers while availing the London bicycle scheme fluctuated between the time range of 18 minute to 25 minutes with an average of 22.88 minutes or 1372.827 seconds. It can be concluded that the time spent by users on the bike has increased in the summer month of June, the highest being 149 hours from 9th June to 15th June (cycling.data.tfl.gov.uk, 2022)
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Duration
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users
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Date Range
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|
Highest
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149.25
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1
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9/6/2021
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15/6/2021
|
|
Lowest
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1
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1756
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9/6/2021
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15/6/2021
|
Table 1: Average length of bike hire
(Source: Developed by learner)
2) Proportion of Bike Journeys Taking Place from or To the “Queen Marys, Mile End” Docking Station.
The probability of bike journeys taking place from and to the station “queen marys, mile end” docking station can be seen to be high in frequency. The number of rides availed during the period of June from the particular station is 370 and 342 rides have been ended to the destination docking station. The total number of rides being 321709 for the week of june.
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No of Rides Availed
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|
Start Station Name
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Queen Mary's, Mile End
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370
|
|
End Station Name
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Queen Mary's, Mile End
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342
|
|
Total
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321709
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Table 2: Proportion of Bike Journeys Taking Place, Mile End” Docking Station.
(Source: Developed by learner)
C) Construction of Confidence Interval
1) Average Length of Bike Hire
Construction of confidence levels for the values of average length of bike ride corresponds to the estimated proportion of intervals of arithmetic mean in a sample survey in comparison to the total duration of hiring of bikes during the period. The mean stands at 22.8804,median at 16 and standard variation at 63.74 at a confidence level of 95 % , an upper ci of 23.100 and a lower ci of 22.66 can be evaluated .
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Average length of bike hire
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Duration (Minutes)
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Mean
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22.88045059
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Standard Error
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0.112385227
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Median
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16
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Mode
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9
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Standard Deviation
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63.74412395
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Sample Variance
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4063.313338
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Kurtosis
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4623.156243
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Skewness
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52.63850303
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Range
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8954
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Minimum
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1
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Maximum
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8955
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Sum
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7360824
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Count
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321708
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Confidence Level(95.0%)
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0.220271819
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Upper CI (95%)
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23.10072241
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Lower CI (95%)
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22.66017878
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Table 3: Confidence Interval of Average Length of Bike Hire
(Source: Developed by learner)
2) Proportion of Bike Journeys
The range of values have been taken into account as sample and confidence level has been analysed at 95 % such that values can be calculated that will reflect a true and fair picture of the demography and their behavioural patterns. This can be analysed to deduce the frequency of trips to and fro the queen marys, mile end” docking station .the construction has been shown in the below table .
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Proportion of bike rides from Queen Mary's Docking Station
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Column1
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Mean
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172
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Standard Error
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5.354126135
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Median
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172
|
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Standard Deviation
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99.15980368
|
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Sample Variance
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9832.666667
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Kurtosis
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-1.2
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Skewness
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3.39592E-17
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|
Range
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342
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Minimum
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1
|
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Maximum
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343
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Sum
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58996
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Count
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343
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Confidence Level(95.0%)
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10.53116228
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|
Upper CI (95%)
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182.5311623
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Lower CI (95%)
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161.4688377
|
Table 4: Confidence Interval of Proportion of bike rides from Queen Mary's Docking Station
(Source: Developed by learner)
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Proportion of bike rides to Queen Mary's Docking Station
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Column 1
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Mean
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186
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Standard Error
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5.567764
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Median
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186
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Standard Deviation
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107.2427
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Sample Variance
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11501
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Kurtosis
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-1.2
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Skewness
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-9.7E-18
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Range
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370
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Minimum
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1
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Maximum
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371
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Sum
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69006
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Count
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371
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Confidence Level(95.0%)
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10.94843
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Upper CI (95%)
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196.9484
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Lower CI (95%)
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175.0516
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Table 5: Confidence Interval of Proportion of bike rides to Queen Mary's Docking Station
(Source: Developed by learner)
- D) Hypothesis of Average Length of Bike Hire:
A Broad Reasoning Could Be Drawn about the Average Length and Duration through the analysis of the following,
The Length of Hiring of Bikes about A Wide Range of the Population can be drawn by The Hypothesis on the Actual Dataset of the Bike hiring provided for the project, for The Period of June.
The computation of the values from the data for the average number of rides per hour could help in formulating the null theory. Certain measurements have been performed to find out the true average number of rides by the registered users during the summer month of June 2021. The significance level has been specified by the construction of confidence level by 95 %. The result of such analysis shows a value of 0.2202. Casual riders avail greater number of rides during the weekends. Therefore, the average number of bike rides on normal working days is equal to the average number of bike rides during the weekends, both performed by the casual riders. Thus, the operating report can be prepared the top five stations can be chosen. Solutions for broken bikes could be well cared of the rides that take less time could be the ones making round trips; an extra condition could be added to make the starting and ending stations identical. Theft and anomalies of docks which are broken could not be considered. Reliable ways for calculation of bike route are to be established without the GPS data from the bike (subscription.packtpub, 2018). Riders performance by age, gender in miles/hour can be established and compared. Predictive or baseline methods are used for analysing the massive dataset and journeys are capped accordingly. dropping of columns which are irrelevant can also help.
- E) Hypothesis Of Proportion Of Bike Journeys:
The results are the intensity of bike sharing of bikes from the usage data has been calculated. the number of trips started from or ended at the dock station of “queen marys, mile end” ,signifying the factors involved behind the could be tourist attractions around the city or the trade dominant regions facilitating growth. Presence of numerous bike stations, market size of the labour force and the population scattering in the regions nearby. Direct comparison between the factors is established from the coefficient of the different stations. the usage patterns are same with the patterns of travelling and the trips are shorter but more diversified into leisure or shifted towards food .the alternate transportation modes have impacts on the usage duration of the bikes but it still considers the inter modal complementary theories with the bike riding issues .
F) The Impacts Of The Covid-19 Pandemic On The Usage Of Bike By People:
The adoption of various methods that could help in the outbreak of the covid19 virus could be seen during the pandemic period having a huge impact on the individual travel behaviours and the transportation systems (heydari and behsoodi, 2021). The lockdown led to a decrease in the usage of the santander London bicycle hire scheme having an impact on the traits of the service such as the duration and the occurring periods. The trips in the morning were shorter and the impact could be seen near the parks, railway stations and the and hospitals at a positive direction. li and ren (2019) stated that the policy makers could resort to the more pragmatic implications for the bike renting scheme for the public.
References
Giglio, C., Musmanno, R. and Palmieri, R., 2021. Cycle logistics projects in Europe: Intertwining bike-related success factors and region-specific public policies with economic results. Applied Sciences, 11(4), p.1578.
Heydari, S., Konstantinoudis, G. and Behsoodi, A.W., 2021. Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London. Plos one, 16(12), p.e0260969.
https://cycling.data.tfl.gov.uk/ (Accessed on 13th April, 2022)
https://subscription.packtpub.com/book/data/9781839211386/1/ch01lvl1sec05/hypothesis-tests (Accessed on 13th April, 2022)
https://tfl.gov.uk/modes/cycling/santander-cycles/what-you-pay (Accessed on 13th April, 2022)
https://twp.duke.edu/sites/twp.duke.edu/files/file-attachments/research_project.pdf (Accessed on 13th April, 2022)
Li, H., Zhang, Y., Ding, H. and Ren, G., 2019. Effects of dockless bike-sharing systems on the usage of the London Cycle Hire. Transportation Research Part A: Policy and Practice, 130, pp.398-411.
subscription.packtpub, 2018 Hypothesis Tests Available at https://cycling.data.tfl.gov.uk/(Accessed on 13th April, 2022)
Tfl.gov.uk, 2022 Santander Cycles Available at: http://www.tfl.gov.uk/modes/cycling/santander-cycles/what-you-pay (Accessed on 13th April, 2022)
twp.duke.edu, 2020, Organizing a Research Project Available at https://twp.duke.edu/news/(Accessed on 13th April, 2022)
