1. Carefully read the CommBank retail business insights report FY18 provided with this as an attachment and answer the below questions.
The CommBank Retail Business Insights Report depends on a subset of a wide-going quantitative review of 2,473 entrepreneurs, managers and decision makers, just as 16 inside and out subjective interviews. This sub-set includes reactions from 262 retailers inside areas including liquor, food, footwear, clothing, hardware and homewares.
Responding to a range of competitive pressure by the Australian retail sector enhances the desire to increase efficiency within their businesses, maintaining a growth in performance. this increases the adoption of an innovative mindset that is vital in decision making.
Retail sector of Australia keeps on responding to competitive pressure range and desiring to drive efficiencies inside their organizations, to keep up or developing their businesses. Subsequently, retailers seem, by all accounts, to be progressively embracing a creative mentality to enhance customer experience, leverage technology, and ensure they maximize the opportunities available. While numerous retailers are creating a generous and auspicious come back from putting resources into noteworthy change inside these zones, there are others yet to outfit the money related and intangible advantages that development can convey.
There has been moderate inspire in the presence of enterprising capabilities and behaviors that help in innovation. Retailers are less disposed than the normal of all ventures to look for and react to circumstances, consolidate advancement into their staff enlisting and assessment forms, or be happy to take chances on dubious endeavors.
2. Regression analysis is a commonly used technique to find relationship among variables. Answer the below questions based on regression analysis.
Regression analysis is well known to give prediction and in forecasting. An instance, in the absence of rain gauges you may want to predict rainfall by the use of regression technique known as OLS.
iii) Draw a scatter plot based on above data. Based on your plot comment on the relationship between height and weight.
The relationship between height and weight is almost perfect. The connection between the height and weight variables involved a high degree of randomness.
iv) Compute the equation of the regression line.
Intercept (a): 13.942585996204
Slope (b): -0.041046774654845
Regression line equation: y=13.942585996204-0.041046774654845x
v) Calculate the R2 value and comment on the goodness of fit.
R=| (-0.18-0) |/0.14=8.2
R2=82%
The goodness of fit between the height and weight of shows that the values have a hogh degree of randomness.
vi)Use an analytical tool of your choice to calculate them with your answer.
R=| (-0.18-0) |/0.14=8.4
3. classification and regression are commonly used processes in business analysis.
i) Briefly explain the difference between classification and prediction.
For an element in a given data set classification determines a categorical class or label whereas prediction, predicts a missing element in a data set.
ii) Give examples for classification methods you know.
An algorithm or a classifier which utilize data to understand a particular output.
A classification tree records, labels and assign variables to discrete classes.
iii) Give at least three examples how clustering can be used in business analytics. In your answer explain each business case could be addressed using clustering.
Cluster analysis is an exploratory information examination instrument which goes for arranging various items into groups such that the level of relationship between two objects is maximal in the event that they have a place with a similar gathering.
Clustering is not dependent on any driving objective function since it generates natural clusters. For instance, to determine customer profit in next 3 months a decision tree is built. Here, the cluster gives an analysis of the portfolio on distinct attributes target.
Clustering technique is used in business analytics for portfolio initial profiling. To build a specific strategy, an objective modelling technique is used, after having a good understanding of the portfolio.
Being one of the widely used modelling techniques in industries, it segments a customer portfolio that is based on transaction behavior, demographics and other behavioral attributes.
References
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., ... & Bloomfield, C. D. (1999). Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. science, 286(5439), 531-537.
Klein, J. P., Rizzo, J. D., Zhang, M. J., & Keiding, N. (2001). Statistical methods for the analysis and presentation of the results of bone marrow transplants. Part 2: Regression modeling. Bone marrow transplantation, 28(11), 1001.
Siemsen, E., Roth, A., & Oliveira, P. (2010). Common method bias in regression models with linear, quadratic, and interaction effects. Organizational research methods, 13(3), 456-476.
Van Barneveld, A., Arnold, K. E., & Campbell, J. P. (2012). Analytics in higher education: Establishing a common language. EDUCAUSE learning initiative, 1(1), l-ll.
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