Interim Progress Report

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Introduction
The project is an exhaustive research as to the reasons why there has been a decline in the sale of Apple iPads. In addition, it aims at devising an appropriate strategy to change the situation. This research is driven by the fact that company’s revenue is determined by the sale of its products. Stark (2015, 20) argues that sales are influenced by factors both within and without. This work hopes to find out the factors leading to a decline in iPads sale. The output is a report that is useful for an enhanced strategic business decisions.
Progress to Date
During the course of my research, there have been factors standing out as having a direct impact on sales such include advertisements. According to Assmus et al. (1984, 70) the intensity with which a company places its adverts reflects on sales. Well organized and clear ads have an effect of improving sales. However, the prevailing economic conditions may limit the targets of the whole process. This is because the state of the economy has a direct bearing on an individual’s monetary capacity. However, though there may be favorable economic conditions and efficient ads, the product may be priced in a range that is too restrictive to for the prospective customers. This is proof that consumption is determined by more than the status of the economy and marketing campaigns. Again, according to Yagan (2014, 12) the competition is a great influence too. Businesses strive for a particular clientele.

One player’s pricing and product status may prove too restrictive contrasted to another play. IPads are products in a market with similar devices such as Android and Microsoft powered devices.
Owing to the fact that Apple Inc. is not the company being associated with, primary research was never done. However, underway is an analysis of the company’s status. This is being done through various analysis methods. These include the SWOT analysis, Porters Five Forces model and Pest analysis. These are aimed at understanding the business environment, competitive advantages and disadvantages, and an acquisition of knowledge on the weaknesses and threats towards Apple Inc. In addition, data from different companies in the same sphere is being collected to determine the pricing differences. This is in a bid to develop a prediction model for the forecast of future sales. This data is meant as a determinant of the relative effect of pricing on sales.
An analysis of the data to test its suitability is one of the pending tasks. According to Allen 1997, 178) data analysis involves techniques of descriptive statistics to check on data distribution. Gelman and Hill (2006, 32) emphasizes that there are different variables at play and therefore, multivariate regression will be used to analyze the variable’s relationships. The significance of the relationship between sales and the independent variables like the competition is to be determined using a T-Test. Besides this, the other tests to be used are the normality test and the F-Test. According Draper and Smith (2014, 78) R programming language will be used for the statistical analysis. This is because it is freely available Dalgaard (2008, 24) emphasizes that it is efficient with large data quantities. All this is to develop a model useful in the forecast of sales while under different economic conditions.
Problems Encountered
Just like any other undertaking, there are challenges being encountered in this project. First is the financial side. For the proper statistical tools for analysis, there is a cost to be incurred. Again, traversing the data has been a timely task. This I intend to simplify by the division of the data and working on it set by set. That is, for those that need loading into the software, do it in phases.
Summary
Finally, I wish to state that this research work is going on as anticipated though the task of determining the reasons behind the decline in sales is not light. It is one that involves huge amounts of data and use of complex statistical tools. The final report is, therefore, an expositive one. Kraemer et al. (2011, 84) argues that developing companies are instrumental in the economies of various states and so is Apple. Inc. The business situation is also indicative of the social condition of the masses. This research is thus a necessary undertaking to help understand the current status and the necessary remedies.
Reference List
Allen, M.P., 1997. Beyond ordinary regression analysis. Understanding Regression Analysis, pp.186-190.
Assmus, G., Farley, J.U. and Lehmann, D.R., 1984. How advertising affects sales: Meta-analysis of econometric results. Journal of Marketing Research, pp.65-74.
Dalgaard, P., 2008. Introductory statistics with R. Springer Science & Business Media.
Draper, N. R., & Smith, H. (2014). Selecting the “Best” Regression Equation. Applied Regression Analysis, 327-368. doi:10.1002/9781118625590.ch15
Gelman, A. and Hill, J., 2006. Data analysis using regression and multilevel/hierarchical models. Cambridge university press.
Kraemer, K.L., Linden, G. and Dedrick, J., 2011. Capturing value in Global Networks: Apple’s iPad and iPhone. University of California, Irvine, University of California, Berkeley, y Syracuse University, NY. http://pcic. merage. uci. edu/papers/2011/value_iPad_iPhone. pdf. Consultado el, 15.
Stark, J., 2015. Product lifecycle management. In Product Lifecycle Management (Volume 1) (pp. 1-29). Springer, Cham.
Yagan, D. (2014). Supply vs. Demand under an Affirmative Action Ban: Estimates from UC Law Schools. doi:10.3386/w20361