MA508 Business Statistics: Globalization and Trade Report Analysis

This report analyzes global trade trends, particularly focusing on Australia and New Zealand, using business statistics. It examines the impact of globalization, technology, and policy on exports and GDP. The report uses data from various sources, including the World Bank and Australian Bureau of Statistics, to illustrate changes in exports, internet usage, and customer preferences. Statistical tools like time series analysis, frequency distribution, and chart representations are used to summarize the data and identify key trends. The report highlights the importance of understanding these trends for business growth and suggests further statistical methods, such as experimental groups and normal distribution, to enhance the analysis. The report concludes that Australia and New Zealand have a strong economic position to grow their exports through globalization and changing trends, and it emphasizes the need for more detailed statistical inferences to provide greater clarity in the changes.

1MA508 BUSINESS STATISTICS; ASSIGNMENT NUMBER AND CAMPUS
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2MA508 BUSINESS STATISTICS; ASSIGNMENT NUMBER AND CAMPUS
Global trade has always been changing and creates an uncertainty of the upcoming technology
and globalization or policy effects (Narula, 2014). Moreover, the environment seems to be
continually involving especially with the landscape in Australia and New Zealand. The
interaction is highly overrated with the continuous and revolutionary impact of the internet in the
international borders determining future rate of economic growth (Mokyr, Vickers & Ziebarth,
2015). The substance relating to the same can be further elaborated based on the efficiency of
certain data and summarization on the upcoming trends.
The changing trends in customer’s preferences have not only eroded the geographical barriers
but even have boosted international trade. Moreover, the megatrends highlight the technology,
changing demands followed by policy and globalization with cheaper cost of inputs. The data on
globalization summarizes the impact on the annual growth rates that encompasses the global
increase in percentage changes across years from 1980 – 2015 (Chart 2, pg 11). As per this
quantitative data, GDP of Australia has been taken from World Bank data derived in 2016 and is
interval in scale ranging from less than 10% to around 25% of exports as GDP. The data is based
on percentage increase through a time series graph dealing with changes in exports of global
GDP (Bhattacharyya & Williamson, 2016). The data could have improved with proper annexure
of changes could have been highlighted with the changes from the average mean using standard
deviation of GDP growth. The explanation can be followed by the ordinal data taken from
Department of Foreign Affairs and Trade for Australia specifying the top 5 exporters in the
interval of 5 years from 1995 (Chart 3, pg 12). It can be seen that since 90’s Japan has one of the
great export markets followed by China (Flanagan, 2017). Hence, it can be predicted that in later
years, Japan and China would be holding the market strong. However, the study can be
experimental and can subject to change based on the different factors that influence the markets.
Conversely, the exports need to be figured from the increasing global demand of primary
products from the market like China. Australia and New Zealand data has been taken from
Australian Bureau of Statistics from June 2016, which is ratio in scale as per the value amongst
goods and services (Chart 11, pg 31). Australian export has been highlighted by more goods
(78%) but the GDP composition shows a contrast with more percentage from services (77%) and
with the similar composition goes with New Zealand as well with total export of NZ$70.9
billion. The doughnut chart represents the population through a subset of exports from GDP
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3MA508 BUSINESS STATISTICS; ASSIGNMENT NUMBER AND CAMPUS
composition. The future of trade is the key to lower process so that goods can have a good
composition among products than services (Buckley & Casson, 2016).
On the other hand, the internet usage in Australia has been increasing from 2011 until date
(Chart 5, pg 13). The source of data is Australian Bureau of Statistics in Internet Service
Provider Survey through Deloitte’s Calculations and the data has ratio scale. As per the data
descriptions, the volume of data downloads have been constantly increasing in New Zealand in
comparison to Australia which has been below 100,000 Tb across 5 years. However, in this case
a probability of likelihood in chances of volume could have created certainty on the decisions
made.
The drivers have been further depicted through different factors and have resulted that the
change in 5 years is especially for the service based industries such that the digital trends and
technology make the top in charts (Kane et al., 2015). The stacked bar chart depicts the
percentage of the ratio scale measurement as per the survey results collected by Chartered
Accountants Australia and New Zealand in 2016. The statistical results have been calculated
using frequency distribution through cumulative percentage that can be further illustrated
through median and Ogive curve. The description of the data is forecasting more changes in
technology, changing preferences and government policy (Feige & Vonortas, 2017). Moreover,
even the sectors agriculture and forestry have less than 50% coverage by all the three drivers and
more than 70% has been seen on information, media and communication.
To conclude, it can be said that the Australia and New Zealand has a strong yet economical
position to grow its exports through globalization, policy and changing trends as per data
summarization. In addition, the statistical tools that could have further benefitted the results are
through experimental group and usage of normal distribution with probability, which further
highlights the deviation in responses. The surveys acted as a key source of data through
Australian Bureau of Statistics and other sources with latest data in 2016 but a statistical
inference of quartiles could have been justified on the data of exports for a more clarity in
changes. The trends can be guided by the time series data for proper investigation on the trends.
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4MA508 BUSINESS STATISTICS; ASSIGNMENT NUMBER AND CAMPUS
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.
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