Statistical Analysis of Australian Exports: A Comprehensive Report

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Statistics and Research Methods for
Business Decision Making
1

Table of Contents
1.......................................................................................................................................................3
(i)..................................................................................................................................................4
(ii)................................................................................................................................................4
(iii)...............................................................................................................................................4
2.......................................................................................................................................................6
(i)..................................................................................................................................................6
(ii)................................................................................................................................................7
(iii)...............................................................................................................................................8
(iv)................................................................................................................................................9
(v).................................................................................................................................................9
(f).................................................................................................................................................9
Question 3....................................................................................................................................10
(i)................................................................................................................................................10
(ii)..............................................................................................................................................10
(iii).............................................................................................................................................11
(iv)..............................................................................................................................................13
(v)...............................................................................................................................................14
(vi)..............................................................................................................................................16
(vii)............................................................................................................................................17
(viii)...........................................................................................................................................18
References...................................................................................................................................19
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1
Australia: Direction of exports
Top 8 export markets for goods and services
S.N
O
Country A$ bn Change in Value
of Export
Change in
Export (%)
2004-05 2014-15
1 China 15.9 90.3 -74.4 -467.92%
2 Japan 28.2 46.6 -18.4 -65.25%
3 United States 13.9 20.5 -6.6 -47.48%
4 Republic of Korea 11 20.5 -9.5 -86.36%
5 India 7.1 12.7 -5.6 -78.87%
6 New Zealand 12.2 12.3 -0.1 -0.82%
7 Singapore 5.8 12 -6.2 -106.90%
8 United Kingdom 9.2 8.6 0.6 6.52%
Subtotal 103.3 223.5 -120.2 -116.36%
(i)
1 2 3 4 5 6 7 8
-80
-70
-60
-50
-40
-30
-20
-10
0
10
-74.4
-18.4
-6.6 -9.5 -5.6
-
0.100000000000
001-6.2
0.6
f(x) = 7.25476190476191 x − 47.6714285714286
R² = 0.517457931990593
Change in Value of Export
Change in Value of Export
Linear (Change in Value of
Export)
3

(ii)
(iii)
In the above table, there is comparison analysis is conducted which drives various value
and data from the information. This analysis identified two perspective of the analysis.
The first perspective of the analysis conducted in solution A identified that there is a
major change in the market of China for the export and also highly influencing market
from the point of Australian business. In other hands, there is a nominal change in the
market of New Zealand from 2004 to 2015 which means Australian are not much
interested in the New Zealand market for their export-import business. In another Hand
graph (b) defines the same as discussed in the graph (a). China is a dominating player
in the graph (b) where they had the fluctuation of approx. 450 % among the year. This
all thing define dependency of the Australian market on one nation which is China for
their import and export activities.
4
1 2 3 4 5 6 7 8
-500.00%
-400.00%
-300.00%
-200.00%
-100.00%
0.00%
100.00%
Change in Export ( %)
Axis Title

2
(i)
Classes Bin Frequency Relative Frequency
30-40 35.00 2.00 0.05
40-50 45.00 4.00 0.10
50-60 55.00 8.00 0.20
60-70 65.00 11.00 0.28
70-80 75.00 8.00 0.20
80-90 85.00 5.00 0.13
90-100 95.00 2.00 0.05
A comprehensive table is constructed for the study in which frequency distribution for
the data set available is calculated. Further Relative frequency also identified which
measure the important facts of sales of the umbrella from 40 days for the shops in
Australia. The whole data table is based on the information given in the assignment for
the sales of the umbrella of the shop from recent 40 days from which various analyses
are conducted in next task of the assignment and identified qualitative result which
helps in better decision making.
5

(ii)
Classes Bin Frequen
cy
Relative
Frequency
Cumulative
Frequency
Cumulative
Relative
Frequency
30-40 35.
00
2.00 0
.05
2.0
0 0.05
40-50 45.00 4.00 0.10 6.00 0.15
50-60 55.
00
8.00 0
.20
14.0
0 0.35
60-70 65.
00
11.00 0
.28
25.0
0 0.63
70-80 75.
00
8.00 0
.20
33.0
0 0.83
80-90 85.
00
5.00 0
.13
38.0
0 0.95
90-100 95.
00
2.00 0
.05
40.0
0 1.00
Further in the task Cumulative and relatively cumulative frequency is calculated which
helps to identify the portions of the sales which are covered by the shops in their daily
routine activities of the business. Relative cumulative frequency Helps Company to
identify which part of the portion is done throughout the process. Further cumulative
frequency helps shops to identify the total number of umbrella sales throughout the
days of working for the shops.
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(iii)
30-40 40-50 50-60 60-70 70-80 80-90 90-100
-
0.05
0.10
0.15
0.20
0.25
0.30
Histogram
Relative Frequency
The histogram is the tool which provides a detailed representation of numeric data to
identify the probable occurrence from them. It can be defined as the probability
distribution of a continuous series of the numbers. In this study, this tool is used to
identify the maximum occurrence for the sales of the umbrella in the shop of Australia
(Spss-tutorials, 2019). Histogram identified that maximum occurrence for umbrella is
from the class of 60-70 in which more than 0.25 share as included. This defines that
shop however sold more than 60 umbrellas in 25% of 40 days of the sops in the market.
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(iv)
0 1 2 3 4 5 6 7 8
-
0.05
0.10
0.15
0.20
0.25
0.30
Relative Frequency
Ogive diagram reflects the graphical representation of relative frequency for the data set
of the research. In the above diagram, relative frequency are represented in ogive
diagram which interprets that 4 Category had the peak point in a number of occurrence
for the company and after that sales of the shop is continuously declined in the market
which can be a major concern for the company. As the sales of the shop are not fixed in
the market which also a worrying concern for the business as they faced a fluctuated
growth and decline for the business. This kind of complexity increased the confusion
among the management for taking a decision for betterment of the company and also
discards from the right path of the business activities.
(v)
From the analysis, it can be identified that the proportion which is less than 60 belongs
to 0.35 from the sample size which is more the one third from the overall population.
When management goes for the count of the number of occurrence of the event it
comes on 14 days on which shop sold good which is less than 60 which means in this
time period shop is not so much profit generate for the business.
(f)
It is identified that approx. 0.37 is the portions of relative cumulative frequency which is
more than 70 for the shops and when it count on a number of days than shops earn
high revenue in the 15 days of working for the shops. During the 15 days, business is
highly profitable and sole umbrella more than 70 per day. This time period is covered
the major part of the profit for the time period of the shop in which they sold their
umbrella in the market.
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Question 3
(i)
In this study, two variables are used to analyze the data in which independent variable
for the study is Final Consumption Expenditure and dependent variable for the study is
retail turnover per capita for the nation as it is dependent of the consumption
expenditure for the nation.
50000 100000 150000 200000 250000
0.0
500.0
1000.0
1500.0
2000.0
2500.0
3000.0
3500.0
Scattor daigram
Scattor daigram
(ii)
In this study, two factors are used for the analysis of the data. Management used Retail
turnover per capita and final consumption expenditure for the research on which retail
turnover per capita is a dependent variable which depends on final consumption
expenditure which is named as the independent variable for the study. This research is
conducted to analyze the relationship between the variable and their impact on another
variable in the market so that management or business can take a major decision in the
context of the export market. Under this assignment various statically tools are used to
analyze the relation of the variable and also guide to identify the relationships among
the variable. It can be major that both are the economical factor which had an
interlinked connection which influences the working of each factor in the market.
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(iii)
Retail Turnover
Particular Amount
Mean 2205.761832
Standard Error 47.45906998
Median 2180.2
Mode 2852.8
Standard Deviation 543.1938837
Sample Variance 295059.5953
Kurtosis -1.611990019
Skewness 0.074657645
Range 1558.7
Minimum 1455.9
Maximum 3014.6
Sum 288954.8
Count 131
Largest(1) 3014.6
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Smallest(1) 1455.9
Confidence Level (95.0%) 93.8920941
Final Consumption
Particular Amount
Mean 146019.855
Standard Error 4098.05042
Median 139137
Mode #N/A
Standard Deviation 46904.331
Sample Variance 2200016262
Kurtosis -1.2960945
Skewness 0.30683061
Range 151259
Minimum 81889
Maximum 233148
Sum 19128601
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Count 131
Largest(1) 233148
Smallest(1) 81889
Confidence Level (95.0%) 8107.50266
(iv)
Correlation analysis is a statically tool which helps t5o determine the relation among the
variable of the survey. The correlation coefficient is the degree of the relation among the
variable from the sample size of the population (FOLEY B., 2018). This defines how
strong both variables are related to each other and the impact which can be imposed by
the change in the variable in the market impacts on other variables.
Correlation analysis
Particular Retail Turnover Final Consumption
Retail Turnover 1.0000 0.9877
Final Consumption 0.9877 1.0000
Correlation analysis identified a strong relation among both variables. This defines that
any significant change in the retail turnover can impact on the rate of final consumption
in the economy for Australia. As the correlation coefficient from the study is 0.98 which
is nearest to 1 that defines that any change had equally impact on the performance on
the dependent variable in the economy.
(v)
SUMMARY OUTPUT
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