Business Statistics Report: Analysis of Global Trade and Exports

This report provides a statistical analysis of global trade, focusing on the economic trends and export data of Australia and New Zealand. It examines various data representations, including trend lines, ordinal data, and charts, to illustrate changes in GDP, export markets, internet usage, and the composition of exports. The analysis covers both descriptive and inferential statistics, utilizing data from sources like the World Bank and the Australian Bureau of Statistics. The report explores factors influencing trade, such as globalization, innovation, and government policy, and concludes with recommendations for future development and statistical methods for enhanced clarity. It highlights the importance of statistical instruments like exploratory gathering and the use of normal distribution with probability to support the outcomes and offers suggestions for future analysis, including the use of quartiles for a clearer understanding of export changes.

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Global trade has dependably been changing and makes a vulnerability of the up and
coming innovation and globalization or strategy impacts (Narula, 2014). In addition, the
environment is by all accounts ceaselessly including particularly with the landscape in New
Zealand and Australia. The cooperation is exceptionally exaggerated with the nonstop and
progressive effect of the web in the universal outskirts deciding future rate of monetary
development (Mokyr, Vickers and Ziebarth, 2015). The substance that is relating with the same
situation can be additionally explained in view of the effectiveness of specific information and
outline on the up and coming patterns.
The changing patterns in customer's inclinations have disintegrated the topographical
hindrances as well as even have supported international trade. On the other hand, the trends
feature the innovation, changes in demands took after by strategy and globalization with less
expensive cost of data sources. The information on globalization outlines the effect on the yearly
development rates that envelops the worldwide increment in rate changes crosswise over years
from 1980 – 2015 (Figure 1). According to this quantitative information, GDP of Australia has
been taken from World Bank information inferred in 2016 and is interim in scale running from
under 10% to around 25% of fares as GDP. The information depends on rate increment through a
period arrangement chart managing changes in fares of worldwide GDP (Bhattacharyya and
Williamson, 2016).

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Figure 1: Exports as a percentage of global GDP
 The variables included in this chart are year (quantitative variables) and the percentage
increase in GDP (quantative variable).
 The data here is an example of descriptive statistics. This is not inferential statistics
because the whole population is considered to conduct the study
 The trend line shows the percentage increase in GDP over the years 1960 to 2015.
 The values are represented using this line as this will show the trend of the GDP over the
years and can be compared very easily.
This data set can be enhanced by applying appropriate changes. These changes can be
enhanced from the changes that occur from the average value by using standard deviations of the
GDP growth. The clarification can be trailed by the ordinal data taken from Department of
Foreign Affairs and Trade for Australia determining the main 5 exporters in the interim of 5
years from 1995 (Figure 2). It can be seen that since 90's Japan has one of the colossal fare
markets took after by China (Flanagan, 2017). Consequently, it can be anticipated that in later

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years, Japan and China would be holding the market solid. In any case, the investigation can be
exploratory and can subject to change in view of the diverse components that impact the business
sectors.
Figure 2: Australia’s top five export markets
 The data in figure 2 is ordinal data.
 The variables included in this chart are year (Quantitative data) and country names
(Qualitative data)
 The numbers show the ranks of the countries with which Australia expresses the most
export relation.
 The year 2025 shows the predictions in the export relation ranks based on the previous
trends.
Then again, the web use in Australia has been expanding from 2011 till now (Figure 3).
The information source in this case is also the Australian Bureau of Statistics in Internet Service
Provider Survey through Deloitte's Calculations and the information has proportion scale.
According to the information depictions, the volume of information downloads have been
continually expanding in New Zealand in contrast with Australia which has been beneath
100,000 Tb crosswise over 5 years. In any case, for this situation a likelihood of probability in
odds of volume could have made sureness on the choices made.

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Figure 3: Growth in demand for data
 The variables involved in this figure are year (Quantative variable) and volume of
monthly download in Tb (Quantative variable).
 The data involves the whole population and not a sample of the population. Thus it is
descriptive statistics and not inferential statistics.
 The trend line shows the amount of increase in internet usage over the years 2011 to
2016.
 The data is shown with the help of multiple line graph as it is easily comparable.
With the trail of the discussions above, the exports should be figured from the worldwide
increase in demand of essential items from the markets like Australia, New Zealand and China.
Information has been taken from Australian Bureau of Statistics from June 2016, which is in the
ratio in scale according to the incentive among merchandise and enterprises (Figure 4).
Australian exports have been featured by more products (78%) yet the composition of the
country’s GDP demonstrates a difference in relation to more rate from administrations (77%)

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and the same composition of GDP runs with the comparative organization New Zealand too
which add up to export of NZ$70.9 billion. The doughnut chart shows the populace through a
subset of exports from GDP synthesis. The eventual fate of trade is the way to bring down
process with the goal that merchandise can have a decent arrangement among items than
administrations (Buckley and Casson, 2016).
Figure 4: Goods and services share of exports and GDP for Australia and New Zealand by
value for the year ended June 2016
 The variables involved in this figure are the export values of goods and services for the
year 2016 (Quantitative variable)
 The data consists of the whole population and not a sample of it. Thus it is descriptive
statistics.
 The data is represented as percentages of the values
 The data has been expressed in this manner in order to make easy comparisons.

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The drivers have additionally being portraying through various factors and have come
about that the adjustment in 5 years is particularly for the administration based ventures with the
end goal that the computerized patterns and innovation make the best in outlines (Kane et al.,
2015). The stacked bar graph delineates the level of the proportion scale estimation. This has
been found out on the basis of the data accumulated by Chartered Accountants of Australia and
New Zealand in 2016. The measurable outcomes have been figured utilizing the table of
distribution of frequency through total rate that can be additionally represented using the median
and the cumulative probability curve or the ogive. The portrayal of the information is
determining more changes in innovation, changing inclinations and government strategy (Feige
and Vonortas, 2017). In addition, even the divisions of forestry and agricultural services have at-
most 50% scope by the three drivers altogether and over 70% has been seen on mass media and
communication and on the information as well.
 The data in figure one contains one variable, changes in drivers. The data is qualitative in
nature.
 The values are shown as percentage of the total values.
 This is survey data and thus, inferential statistics can be computed on this data in order to
represent the whole population from the sample.
 The data has been expressed in this form to make easy comparisons of the respective
categories and the effects of the drivers in each of them.
Top ranked drivers of change over the next five years by industry

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In view of closing this discussion, it can be concluded that, the countries Australia and
New Zealand has a solid yet conservative position to develop its export facilities through
globalization, approach and changing patterns according to information outline. Also, the
measurable instruments that could have additionally profited the outcomes are through
exploratory gathering and use of ordinary appropriation with likelihood, which additionally
features the deviation in reactions. The overviews went about as a key wellspring of information
through Australian Bureau of Statistics and different sources with most recent information in
2016 however a measurable deduction of quartiles could have been supported on the information

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of fares for a greater clearness in changes. The patterns can be guided when arrangement
information for appropriate examination on the patterns.

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References
Bhattacharyya, S., & Williamson, J. G. (2016). Distributional consequences of commodity price
shocks: Australia over a century. Review of Income and Wealth, 62(2), 223-244.
Buckley, P. J., & Casson, M. (2016). The future of the multinational enterprise. Springer.
Feige, D., & Vonortas, N. S. (2017). Context appropriate technologies for development:
Choosing for the future. Technological Forecasting and Social Change, 119, 219-226.
Flanagan, S. (2017). Building resilience in Japan-China ties: a role for Australia.
Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2015). Strategy, not
technology, drives digital transformation. MIT Sloan Management Review and Deloitte
University Press, 14.
Mokyr, J., Vickers, C., & Ziebarth, N. L. (2015). The history of technological anxiety and the
future of economic growth: Is this time different?. The Journal of Economic
Perspectives, 29(3), 31-50.
Narula, R. (2014). Globalization and technology: Interdependence, innovation systems and
industrial policy. John Wiley & Sons.