Business Statistics Quantitative Methods

Question: Discuss about the Business Statisticsfor Quantitative Methods. Answer: Introduction The selected article tends to highlight the retail trade data for January 2017. Further, using various statistical tools and techniques, an analysis of the retail trade has been carried out which seeks to identify the various causal factors that are responsible for the witnessed trend. Additionally, a more detailed breakup of the various constituent categories and the underlying trends have also been highlighted. In wake of the above article and the findings contained therein, the objective of the given essay is to highlight the usage of various statistical techniques, variation measures, summarization and description of the data presented in the given article. Besides, suggestions have also been offered on how improvements can be done so as provide better and more relevant analysis of the given data. Analysis The given article tends to capture the trends with regards to retail trade in Australia in January 2017. Also, analysis of the same has been provided by taking into consideration the key determinants particularly consumer confidence. Since, all the data included in the given article is of numerical type where clear definition of zero exists, hence the appropriate data type is ratio. Further, the increase in various parameters is expressed using percentage which tends to draw a comparison of the current value with the previous value in order to derive meaningful information about economic growth (Flick, 2015). The visual approach to data presentation has been relied on where the relevant data is presented in the graphical form so as to enable the reader to make it understandable. In this respect, the corresponding data in the same month of the previous years has been presented so as to allow the reader to draw conclusions. Besides, the annual trend in the movement of retail trade has also been captured for various states so as to highlight the retail trade trend at the level of various states which improves the overall understanding or users. Finally, the movement of the key components of retail trend has also been graphically captured in order to draw conclusion about the contributory factors in the movement of retail trade value (Eriksson Kovalainen, 2015). The given article uses descriptive statistics since the focus is on describing the actual trends with regards to retail trade and to facilitate a comparison using various measures of descriptive statistics. Inferential statistics does not have any relevance here as the data in itself is essentially population data which is computed using pre=determined formula. Thus, the objective here is to present the retail trade data for January 2017 and allow the user to draw conclusions through the use of descriptive statistics which is limited not only to the current period but goes back to the historical period so as to allow the formation of time series which would allow the users to put the current data into perspective (Hair et. al., 2015). In the given article, emphasis is given on drawing the relationships between retail trade and the respective contributory factors in a bid to explain the relative movement by developing a causal relationship of retail trade with factors such as consumer confidence, household savings rate along with tourism. However, no exact model has not been developed to explain the relationship between these variables which is not necessary as the impact of these variables on retail spending and retail trade is already established in the available literature. Thus, focus has been more on the directional movements relying on the underlying correlation between the data (Fehr Grossman, 2003). For instance, a higher consumer confidence would result in higher retail spending and higher value of retail trade. Yet, another example is the tourism industry where a higher number of tourists would provide a boost to the retail sales. Thus, there seems to be correlation between the above mentioned two variab les and the relationship is upward sloping and positive. Thus, relying on these established relationships, the article tends to go beyond merely stating the fact s and aims to put things into perspective. With regards to the improvements in the information presented, the data about the exact variation in the retail trade data when compared annually and also using the corresponding months from previous years may also be represented. This would allow the users to understand the variability in the retail trade and to decipher the stability in the economy (Hastie, Tibshirani Friedman, 2011). A stable and growing economy would result in consistent growth of the retail trade while a economy passing through a turbulent phase would tend to show variations on either sides which tends to dampen the overall investor confidence in the economic growth going forward. Additionally with regards to presentation, a pragmatic suggestion would be to club the various graphs with their corresponding explanation in a tabular form so as to ensure that the presentation becomes more systematic. Summary It is apparent from the above discussion that the current article deals with the presentation of retail trade data corresponding to January 2017. Since all the data can be numerically expressed and have a well defined absolute zero, hence the data type deployed is essentially ratio type. Further, visual presentation has been given focus so as to facilitate understanding in a minimal amount of space available while making it interesting for the users. The article has used only descriptive statistics and based on the various available data, logical conclusions have been drawn. In this regard, causal relationship between the various determinants of retail trade and factors measured has been utilized to offer explanation to the users. For improving the given data, presentation is one aspect while variation of the retail trade in an appropriate time series may be imperative for the relevant stakeholders to understand the underlying economic stability. References Eriksson, P. Kovalainen, A. (2015).Quantitative methods in business research (3rded.). London: Sage Publications. Fehr, F. H., Grossman, G. (2003).An introduction to sets, probability and hypothesis testing (3rded.). Ohio: Heath. Flick, U. (2015).Introducing research methodology: A beginner's guide to doing a research project (4thed.). New York: Sage Publications. Hair, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., Page, M. J. (2015).Essentials of business research methods (2nded.). New York: Routledge. Hastie, T., Tibshirani, R. Friedman, J. (2011).The Elements of Statistical Learning (4thed.).New York: Springer Publications.