This unit uses three modes of assessment, explained in detail below:

Assessment 1 - Exam

Link to Module Learning Outcomes

This assessment evaluates the following unit intended learning outcomes (ILO):

•    ILO1:   Demonstrate  an   understanding  of  what   business  analytics   is,  how  it  benefits organisations, how it impacts sustainable development, and when and how it should be used.

•    ILO2: Demonstrate an understanding of the meaning and use of mathematical and statistical concepts which are essential for the successful application of business analytics.

Preparation

•    The exam will consist of multiple-choice questions.

•    For the  short  multiple-choice questions, there is one correct answer out of a number of options per question (typically four options).

•    Revision of the core textbook beyond the content of the lecture slides is essential.

Submission

This unseen exam will be carried out remotely, and further details will be provided closer to the time. The examination will open at 20th  October 2023 12:00 to 13:00 GMT.

Assessment Weight

40% of the total unit mark

Marking Criteria

This assessment will be marked using the following criteria.

Assessment 2 – Individual Coursework

Link to Module Learning Outcomes

This assessment covers the following module learning objectives:

•    ILO3:  Prepare  data  for  analysis  and  assess  the  quality  of data  based on  how  it was collected.

•    ILO4:  Explore  and  communicate  the information contained in data to answer business questions effectively.

Assessment Instructions

The purpose of this assessment is to test your ability to prepare data for analysis (ILO3) and to explore  and  communicate  the  information  contained  in  data  (ILO4)  through  a  written  report documenting their approach to solving a business problem using data. For this assessment, you are to develop a report from a (group) data analytics project analysing a data set using appropriate data analytics approaches to make predictions about future outcomes. Therefore, you are required to produce a 1,500-word business report, which should describe the methodologies and results of data exploration and analyses you have conducted.

Important information about the report

The report should be 1,500 words (+/- 10%) in length. Please keep in mind the following points:

•    This is not an essay assignment. You should not describe or analyse theory and models in isolation. You will be assessed primarily on how you apply the concepts and models from this  module  to  a  real  operation,  evaluate   its  effectiveness,   identify  and   recommend improvements that could be made.

•    However, you should include academic references where relevant e.g., the source of models used  in  your  report,  supporting  data. Please  note  that  you  cannot  cite  the  lecture slides! Any quotations from such sources should be properly referenced including page numbers using Harvard referencing style, with full details included in the references section.

•    It is recommended that your work should have between 10 to 20 references. Please use Harvard referencing throughout.

•    Throughout the report, you will need to focus on both the presentation and clarity of any models, diagrams and tables, as well as the quality of your analysis. Consider how to best present your portfolio to make it look as professional as possible e.g., using a contents page.

•    Tables and Figures must be labelled with a caption, “Figure 1: Diagram of….” etc. with the text referring to the Figure, or table, as Figure 1, etc.

•    Reading beyond the course materials is vital.

•    The use of graphs and diagrams to illustrate your analysis is strongly encouraged.

•    You are reminded that this assignment is about Business Analytics, not data science nor statistics. The mathematical justification and specific number of analyses you applied is not as important as your ability to conduct a clear analysis of the business implications of those data analytics technique.

Report Structure

Please note that the structure below is the recommended format for the assessment.

1.   Title of the report

•    The title should be informative and concise.

2.   Introduction

•    Provide brief background information of your chosen company and competitors.

•    Highlight the objectives of the data analysis.

•    A quick map/outline of the report (how the report is structured).

3.   Main body – Methods, Results/Findings and Discussions

•    Data Collection

o Describe the data collection process (e.g., what data is collected, what variables are selected and from which database etc.).

o Illustrate steps for data cleaning and how the final sample is created (e.g., how did you deal with the missing values) | Note: This is likely to cover part of your response to Q4 |

•    Data Description and Summary

o Report the results for Q1 and Q3.

o Present  descriptive  statistics  of  the  key  indicators  required  in  Q3  (e.g.,  mean, standard deviation, minimum/maximum values etc.) and relevant findings on the indicators.

4.   Results/Findings and Discussion

•    Present and interpret data analysis results for Q1.

•    Discuss  findings  based  on the  data evidence and the  provided theory  in the readings. Critically evaluate your model and results with wider literature. Q1 and Q5.

5.   Conclusions

•    Summarize the major findings and your conclusions drawn from the data analysis.

•    Identify the limitations of data analysis in the report and suggest for future research.

6.   References

•    List the works or  resources you have referred to  in the report or used to research (e.g., books, academic articles, industry report, websites, etc.)

•    Harvard referencing style (Note: reference list and in-text citations)

You should also make sure that you are fully aware of the School's policy on plagiarism. You should be aware that you cannot later claim that you did not know the rules and regulations. Copying material from similar essays that can be found on essay websites is not acceptable and can lead to disciplinary         action.          See          https://www.bristol.ac.uk/students/support/academic- advice/academic-integrity/plagiarism/  for full information.

Various websites claim that they help students by showing them what is expected on a typical assignment such as in Business Analytics. These tacitly encourage plagiarism and copying, which does not demonstrate true understanding. It is more important to develop your own voice and your own abilities in writing and research, and to show that you can see how operations function in any real-world setting. All assignments are scanned via plagiarism detection software

Submission

Each student must submit their completed portfolio assignment electronically via Canvas.