Analysis of Fatalities in Australia

Analysis of fatalities in Australia
Prepared by
Firstname Lastname
University of the Sunshine Coast
Queensland
May-June 2019

1. Introduction
1.1 Authorization and Purpose
This study sought to analyze the trends in fatalities in Australia. The aim was to
analyze and compare the trends based on the states as well as the gender. The
question that this study seeks to answer is how does the trend in fatalities compare for
the males and states? The findings of this study are crucial in informing the
government as well as other stakeholders on how to come up with measures that
would see the reduction in the fatalities.
1.2 Limitations
The main limitation of this study is the fact that the collected data is only for one
country which is Australia. There is therefore no comparison that is being made to
understand the trends in other countries.
1.3 Scope
Secondary data collected from the World bank database is utilized for this study.
Before analysis is done the dataset is pre-processed ready for analysis. Both
univariate and bivariate analysis are performed for this study. Other advanced
analysis involving regression analysis as well as cluster analysis are also performed.
1.4 Methodology
The study involves analysis of panel data. The data spans from 2010 through to 2018
and involving six states in Australia as well as two territories.
2. Data setup
The pre-processed data was loaded into R for analysis. The code used to load the data
into R is given below;

The necessary packages such as cluster package
were loaded into R. The code is presented below;
3. Exploratory Data analysis
3.1 One variable analysis
3.1.1 One variable analysis 1
The codes are presented below;
In this section, we present the summary statistics for Age. As
can be seen, the average age of the victims was found to be 43.77 with a median age being 41.00.
Since the median and the mean age are close to each other we can say that the distribution is
close to normal distribution. This is confirmed form the boxplot given below;
Figure 1: Box plot of speed limit
fatalities<-read.csv("C:\\
Users\\Documents\\
fatalities.csv")
install.packages("cluster")
library(cluster)
summary(fatalities$Age)
boxplot(fatalities$Age,
ylab="Age",
main="Boxplot of age",
col=" chartreuse1 ")

3.1.2 One variable analysis 2
In this section, we present the frequency distribution of the speed limit using a histogram as well
as a summary statistics for the variable speed limit.
The code used to generate the results is given below;
The average speed limit is 83.17 with the highest speed limit
being 130 and the median speed is 80.00.
Figure 2: Histogram for speed limit
As can be seen from the histogram above (figure 2) majority of the fatalities came from speed
limits between 90-100. Speed limits of 50 to 60 also had a substantial fatalities of more than
2000 cases.
3.2 Two-variable analysis
3.2.1 Two-variable analysis 1
>
summary(fatalities$Spee
d.Limit)
Min. 1st Qu. Median
Mean 3rd Qu. Max.
15.00 60.00 80.00
83.17 100.00 130.00