Statistics Assessment: Car Accident Fatalities in London and SE

This statistics assignment analyzes car accident fatalities in London and the South East region during 2017. The student constructed a frequency distribution table and calculated the mean, median, and mode to summarize the data. The analysis revealed that most suburbs experienced low car accident-related fatalities, with a median of 3. The student also calculated the standard deviation, created a cumulative frequency diagram, and a histogram to visualize the data. The analysis concluded that while the majority of local authorities had low fatality rates, some areas had higher incidences, warranting further investigation. The assignment fulfills the requirements of the brief, which includes the use of a dataset of at least 50 observations, and the creation of various statistical representations.

STATISTICS
STUDENT ID:
[Pick the date]

Introduction
The objective of the given statistical analysis is to provide information about the reported
fatal causalities in car accidents in various suburbs belonging to London and South East
region in 2017. Using the information provided, the analysis has been performed for the data
using appropriate statistical tools
Analysis
The relevant data corresponds to fatalities data for 53 suburbs located in London and South
East region during the year 2017. The source of the data is
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/
attachment_data/file/755698/rrcgb-2017.pdf
(i) Frequency distribution table
It is evident that there are three suburbs with no fatalities in car accidents in 2017. While for
most suburbs the incidence of car accidents linked fatalities is low but there are some suburbs
where the incidence is more than 30 in a single year i.e. 2017.
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(ii) Mean, Median and Mode
Mean
x = Σ f x
Σ f = 398
53 =7.51
Median
Σ f +1
2 =53+1
2 = 54
2 =27 thterm
Median = 3
Mode
Maximum frequency has been observed for 3 and hence, mode is 3.
Mode = 3
It can be concluded that 50% of the suburbs included in the given dataset had annual fatalities
related to car accidents lower than or equal to 3 in 2017. The average fatalities is higher as
the average seems to be influenced by the higher values recorded in certain suburbs which
tends to distort the mean.
(iii) Standard deviation
3

σ = √ Σ( xi− x)2
Σ f = √ 5421.988
53 =10.11
(iv) Cumulative frequency diagram
0 1 2 3 4 5 6 7 8 9 10 12 21 22 24 26 33 36 60
0
10
20
30
40
50
60
Reported Fatal Casualities in 2017
Reported Fatal Casualities
Cumulative Frequency
(v) Graph
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Histogram for representing the reported fatal casualties for chosen suburbs for 2017
belonging to London and South East region is represented below.
It is evident from the above histogram that a vast majority of suburbs and local areas tend to
have car related fatalities lower than 10 in 2017. There are only a handful of local authorities
and suburbs which have a higher incidence of car related fatalities. It would be worthwhile to
understand the potential reason for the same.
Conclusion
Based on the above analysis, it would be fair to conclude that in majority of the local
authorities located in London and South East regions witnessed very low car accident related
fatalities in 2017. This is apparent from the median value of 3. Further, the histogram and
cumulative frequency also confirmed the same. However, there are some local authorities
where the incidence was much higher which would need further analysis so that apt
measures can be taken to lower the incidence of car accident related fatalities.
Appendix
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DATA
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