Reference no: EM132217172

Assignment - Annual survey of supermarket performance

Learning Outcome (ULO)

ULO2: Manipulate and summarise data that accurately represents real world problems
ULO3: Interpret and appraise statistical output to assist in real-world decision making

Overview

The purpose of this assignment is to investigate a dataset utilising the knowledge learned in Modules One and Two. This will enable conclusions to be drawn that ultimately assist in decision making.

The assignment requires you to analyse a given dataset, interpret the results, and then draw conclusions such that you are able to reply to specific questions being asked of you in the form of a report. (These questions are asked in the following memorandum).
The aims of the assignment is to:

- provide you with some examples of the application of data analysis within anorganisation
- test your understanding of the material in the relevant topics
- test your ability to analyse and interpret your results
- test your ability to effectively communicate the results of your analysis to others

Before tackling the assignment, make sure you have prepared yourself well. As a minimum, please read the relevant sections of the prescribed text and listen/watch the pre-recorded material for Modules 1 and 2.

Scenario

FOODplus is one of Australia's leading supermarket chains. There are 750 stores in the chain. Originating from a family based chain of general stores, FOODplus now has supermarkets all over Australia, with the first one being established 27 years ago. In terms of operation, each state capital has a company office and these have significant autonomy in the state's operations. Further, individual store management has wide-ranging powers about day-to-day operations of individual stores. However, broad company planning and direction take place in the company Head Office in Melbourne. Included in the Head Office, is the Research and Analysis Department. A principal role of the department is to provide advice on matters affecting the company. This advice ranges from market research, new product development, advertising strategies, quality control, warehouse management, inventory control, product distribution and new store design.

Requirements:

• Your report should be no longer than 2000 words and there is no need to include, Charts and Tables, or Appendices in the report
• Your Charts/Graphics and Tables are only to be placed in the Data Analysis file i.e. the Excel spreadsheet
• The report is to be written as a stand-alone document (assume Paul will only read your report). Thus, you should not have any references in the report to your data analysis output. Eg. "According to Table 1 in the analysis..."
• Your report must have an informative title
• Your report must contain an executive summary that explains in plain language what the report is for and summarises the main findings. The executive summary should be no more than 2/3 page
• The body of your report must be set out in the same order as in the originating memorandum from Paul Anderson, with each section (question) clearly marked
• Use plain language and your explanations succinct. Avoid the use of technical or statistical jargon as Paul Anderson will not necessarily understand statistical terms. As a guide to the meaning of "Plain Language", imagine you are explaining your findings to a person without any statistical training (e.g. someone who has not studied this unit). What type of language would you use in this case?
• Marks will be lost if you use unexplained technical terms, irrelevant material, or have poor presentation/ organization
• All Microsoft Excel data analysis output associated with each question in the Memorandum is to be placed in the corresponding tab in the yourstudentid.xlsx file

Data Analysis Instructions/Guidelines

In order to prepare a reply to Paul's memorandum, you will need to examine and analyse the dataset
FOODplus_Stores_2018.xlsx thoroughly.

Paul has asked a number of questions and your Data Analysis output (i.e. your charts/tables/graphs) should be structured such that each question is answered on the separate tab/worksheet provided in your Excel document. There are also extra tabs in FOODplus_Stores_2018.xlsx called CI, SampleSize and HT and you should use the various templates contained in these tabs in your "Confidence Interval", "Sample size" and "Hypothesis Testing" answers.

In order to effectively answer the questions, your Data Analysis output needs to be appropriate. Accordingly, you'll need to establish which of the following techniques are applicable for each question:

• Summary Measures (Descriptive Statistics, Inc. Outlier detection)

• Comparative Summary Measures (i.e. Descriptive Statistics for multiple values of a variable)

• Suitable tables and charts or graphics (Module One) that will illustrate more clearly, other important features of a variable

• Scatter diagrams, Correlation analysis and Cross Tabulations (sometimes called Contingency Tables), used to establish the relationships (dependencies) between two variables

• Confidence Intervals: You can assume that a 95% confidence level is appropriate. We use Confidence Intervals when we have no idea about the population parameter we are investigating. Additionally, we would use Confidence Intervals if we are asked to provide an estimate of a population parameter.

• We Use Hypothesis Tests when we are testing a Claim, a Theory or a Standard. Use 5% significance in any hypothesis tests you perform, and provide a summary of your conclusions. Where appropriate, make comparisons with other levels of significance (2%, 1%).

• Sample size calculation: You can assume that a 95% confidence level is appropriate. You may include comparisons for 90% and 99% and a recommendation for the appropriate sample size.

• To answer some questions you may need to make certain assumptions about the data set we are using. Mention these in your data analysis, where relevant. There is no need to mention this in the memo.

Attachment:- Foundation Skills in Data Analysis.rar