MIS771 - Descriptive Analytics and Visualisation

Background 

Assignment Two is an individual assignment. You need to analyse the given dataset and then  interpret and draw conclusions from your analysis. You then need to convey your findings in a  written report to an expert in Business Analytics.  

Percentage of the final grade	35%
The Due Date and Time	8 pm Thursday 16th September 2021

Submission instructions 

The assignment must be submitted by the due date electronically in CloudDeakin. When submitting  electronically, you must check that you have submitted the work correctly by following the  instructions provided in CloudDeakin. Please note that we will NOT accept any paper or email copies or part of the assignment submitted after the due date. 

Information for students seeking an extension BEFORE the due date 

If you wish to seek an extension for this assignment before the due date, you need to apply directly  to the Unit Chair by completing the Assignment and Online Test Extension Application Form before  Thursday 5 pm 16th September 2021. Please make sure you attach all supporting documentation and  a draft of your assignment. The request for an extension needs to occur as soon as you become  aware that you will have difficulty meeting the due date. 

Please note: Unit Chairs can only grant extensions up to two weeks beyond the original due date.  Therefore, if you require more than two weeks or have already been provided with an extension by  the Unit Chair and require additional time, you must apply for Special Consideration via  StudentConnect within three business days of the due date. 

Conditions under which an extension will usually be considered include: 

• Medical – to cover medical conditions of a severe nature, e.g. hospitalisation, severe injury or  chronic illness. 

Note: temporary minor ailments such as headaches, colds, and minor gastric upsets are not  severe medical conditions and are unlikely to be accepted. However, severe cases of these  may be considered. 

• Compassionate – e.g. death of a close family member, significant family and relationship  problems. 
• Hardship/Trauma – e.g. sudden loss or gain of employment, severe disruption to domestic  arrangements, a victim of crime. 

Note: misreading the due date, assignment anxiety, or multiple assignments will not be accepted as  grounds for consideration.

Information for students seeking an extension AFTER the due date 

If the due date has passed, you require more than two weeks, or you have already been provided  with an extension and require additional time, you must apply for Special Consideration via  StudentConnect. Please be aware that applications are governed by University procedures and must  be submitted within three business days of the due date or extension due date. 

Please be aware that in most instances, the maximum amount of time that can be granted for an  assignment extension is three weeks after the due date, as Unit Chairs are required to have all  assignments submitted before results/feedback can be released back to students. 

Penalties for late submission 

The following marking penalties will apply if you submit an assessment task after the due date  without an approved extension: 

• 5% will be deducted from available marks for each day, or part thereof, up to five days. 
• Work submitted more than five days after the due date will not be marked; you will receive  0% for the task. 

Note: 'Day' means calendar day. 

The Unit Chair may refuse to accept a late submission where it is unreasonable or impracticable to  assess the task after the due date. 

Additional information: For advice regarding academic misconduct, special consideration,  extensions, and assessment feedback, please refer to the document "Rights and responsibilities as a  student" in the "Unit Guide and Information" folder under the "Resources" section in the MIS771 CloudDeakin site.

Assurance of Learning 

This assignment assesses the following Graduate Learning Outcomes and related Unit Learning  Outcomes: 

Graduate Learning Outcome (GLO)

Unit Learning Outcome (ULO)

GLO1: Discipline-specific knowledge and  capabilities - appropriate to the level of  study related to a discipline or   profession.  GLO2: Communication - using oral, written and  interpersonal communication to inform,  motivate and effect change  GLO5: Problem Solving - creating solutions to  authentic (real world and ill-defined)   problems.  GLO6: Self-Management - working and learning  independently, and taking responsibility  for personal actions

ULO 1: Apply quantitative reasoning skills to  solve complex problems.  ULO 2: Plan, monitor, and evaluate own  learning as a data analyst.  ULO 3: Deduce clear and unambiguous  solutions in a form that they useful for  decision making and research purposes  and for communication to the wider   public.

 

Feedback before submission 

You can seek assistance from the teaching staff to ascertain whether the assignment conforms to  submission guidelines. 

Feedback after submission 

An overall mark, together with feedback, will be released via CloudDeakin, usually within 15  working days. You are expected to refer and compare your answers to the feedback to understand  any areas of improvement.

The Case Study 

The B-Craft is a South Australian micro-brewery company  

with fifteen years of experience in brewing ale. Although 

its operations are limited to Adelaide and regional South  

Australia, the company has been financially successful. 

B-Craft beer is sold directly to their customers (pubs, bars,  

restaurants and bottleshops) or indirectly through an  

external distribution network. 

Despite their successful operations and solid financial turnovers in the last two years, B-Craft is  forecasting a shift in business climate within the next five years. Now more than ever, B-Craft management feels the need to ensure a strong relationship with its customer base. In addition, they  are planning to put in place a formal procedure to forecast their beer production. The formal  forecasting would help B-Craft with production planning. 

B-Craft approached BEAUTIFUL-DATA (a market research company) and asked them to conduct a  large-scale survey of their customers to better understand the characteristics of B-Craft's customers  and their repurchase intention. 

Data  

Subsequently, BEAUTIFUL-DATA contacted B-Craft's customers and encouraged them to participate  in an online survey. B-Craft's customers rated the company on nine attributes using a 1 – 10 scale in  the survey. They also indicated the likelihood of recommending B-Craft to others. The survey data  was supplemented by information such loyalty duration, type, region, and distribution channel in B Craft's database. 

A complete listing of variables, their definitions, and an explanation of their coding is provided in the  A2T22021.xlsx file.

Appendix- A: Explanatory Notes 

To accomplish allocated tasks, you need to examine and analyse the dataset thoroughly. Below are  some guidelines to follow: 

Task 1. – Assignment planning and execution  

The purpose of this practical task is to help you keep track of your progress with the project and  complete it on time. To report how you plan your project and turn the plan into action, you must  complete the tables provided in dot points as clearly as possible. Remember, effective planning,  execution, and completing given tasks on time are essential professional development skills.  

Note: Dot point writing requires you to use 'point form', not complete sentences. Task 2. – Model building  

You should follow an appropriate model building process. You should include all steps of the model building activities (especially all relevant pre and post model diagnostics) in your analysis.  You can have as many Excel worksheets (tabs) as you require to demonstrate different iterations  of your regression model (i.e., 2.2.a., 2.2.b., 2.2.c. etc.). If you make any reasonable/realistic  assumption about the parameters, please note them next to the analysis. 

Your technical report should clearly explain why the model might have undergone several  iterations. Also, you must provide a detailed interpretation of ALL elements of the final model/regression output. 

Task 3. – Interaction effect 

To accomplish this task, you need to develop a new regression model using ONLY the factors  discussed in the team meeting (Item 3). If you make any reasonable/realistic assumptions about  the parameters, please note them next to the analysis. 

Your technical report should clearly explain the role of each variable included in the model and  use visualisation to illustrate the interaction effect. Make sure you interpret all relevant outputs  in detail and provide managerial recommendations based on the results of your analysis.  

Task 4.1 – Model building  

You should follow an appropriate model building process. You should include all steps of the  model building activities (especially all relevant pre and post model diagnostics) in your analysis.  You can have as many Excel worksheets (tabs) as you require to demonstrate different iterations  of your regression model (i.e., 4.1, 4.1.a). If you make any reasonable/realistic assumptions about  the parameters, please note them next to the analysis. 

You are required to discuss all details of your predictive model/logistics regression output.

MIS771 Descriptive Analytics and Visualisations Page 7 of 9 

Task 4.2. – Visualising and interpreting predicted probabilities 

Your technical report must include the predicted probability visualisation and the practical  recommendations. These recommendations should broadly answer the following question: 

"How a change in perceptions of quality (scores from 1 to 10) and brand image (scores of 1, 5, and 10) may affect the predicted probability of recommending B Craft by two customer segments (i.e. those purchasing directly, and those  purchasing through sales representative)." 

Task 5. – Forecasting Production 

Past quarterly beer production numbers are in the Excel file. Your job is to develop a suitable  model to forecast Quarterly production volumes for the next four quarters. 

In your technical report, you must explain the reason for selecting the forecasting method to  forecast future beer production. The report also must include a detailed interpretation of the  final model (e.g. a practical interpretation of the time-series model…etc.) 

Task 6. – Technical report 

Your technical report must be as comprehensive as possible. ALL aspects of your analysis and  final outputs must be described/interpreted in detail.  

Remember, your audience are experts in analytics and expect a very high standard of work from  your report. High standards mean quality content (demonstrated attention to details) as well as  an aesthetically appealing report.  

Note: The use of technical terms is encouraged and expected in this assignment. 

Your report should include an introduction as well as a conclusion. The introduction begins with the purpose(s) of the analysis and concludes by explaining the report's structure (i.e., subsequent  sections). The conclusion should highlight the essential findings and explain the main limitations. There is no requirement for a table of content or an executive summary.

Appendix-B: Submission Guidelines 

The assignment consists of three documents: 

• Planning and execution tables 
• Analysis 
• Technical Report 

1) Assignment Planning and Execution Tables 

The planning and execution details should be submitted in the appropriate tables provided. The  tables should be in dot points. Before filling in the tables, students are strongly encouraged to watch  the pre-recorded workshop called 'How to plan an assignment and turn the plan into action?' by a  Language and Learning Adviser. 

Note: Give the assignment planning and execution file the following name  

A2_Planning_YourStudentID.docx  

2) Analysis  

The analysis should be submitted in the appropriate worksheets in the Excel file. Each step in the  model buildings should be included in a separate tab (e.g. 2.1.a., 2.1.b., …; and 3.2.a. 3.2.b., …). Add  more worksheets if necessary.  

Before submitting your analysis, make sure it is logically organised, and any incorrect or unnecessary  output has been removed. Marks will be deducted for poor presentation or disorganised/incorrect  results. Your worksheets should follow the order in which tasks are allocated in the minutes of the  team meeting document. 

Note: Give the Excel file the following name A2_YourStudentID.xlsx (use a short file name  while you are doing the analysis). 

3) Technical Report  

Your technical report consists of four sections: Introduction, Main Body, Conclusion, and  Appendices. The report should be approximately 2,500 words.  

Use proper headings (i.e., 2., 2.1., 2.2., …) and titles in the main body of the report. Use sub-headings  where necessary.  

Visualisations / statistical output allowed in the report are: 

1. Interaction effect plots 
2. Predicted probability plots. 

All other visualisations should ideally be in the Appendices (appendices are not included in the word  count).  

Make sure these outputs are visually appealing, have consistent formatting style and proper titles (title, axes titles etc.), and are numbered correctly. Where necessary, refer to these outputs in the  main body of the report.  

Note: Give the report the following name A2_YourStudentID.docx.