Business Statistics and Data Analytics of IBM

Unit Title: Business Analytics

Unit Code:

5Z7Z0004_1819_NZ5F

Core: Y (& Option)

Level: 7

Assignment Title: Business Statistics

Submission Instructions: Moodle / Turnitin

Feedback Return Information: Summary feedback handed to student

Assignment Task

A maximum of 3,000 word report

Unit Learning Outcomes Assessed.

On successful completion of this unit students will be able to:

1. Evaluate sources and types of information that could aid an organisation.
2. Employ relevant statistical techniques for a variety of organisational needs.
3. Identify specific issues relating to the implementation and on going usage of advanced statistical techniques

World classNameProfessional Skills Assessed.

1. Understanding how statistical analysis can effectively be applied to support business decision-making.

Assignment Details and Instructions.

Overview

Students must select a ‘real world’ organisation on which to focus their report for this assessment. It is entirely up to the student as to which one they choose.

Brief

An organisation is about to plan on a project to analyse their business data on supporting business decision-making alongside the formation of a business analytics department at its corporate headquarters.

In your role as a Business Data & Analytics Consultant you have been employed by the organisation to advise them on the processes of data analytics for business decision-making and potential for the business implementation.

You will prepare a maximum 3,000 word report for the organisation on the following areas:

1. Describe a business context with available data and information to the organisation, identify a specific business decision-making issue which could be supported by data analysis.
2. Summarise available and feasible statistical methods to the available data and explain their suitability to the data.
3. Explain how to analyse the data using SPSS tool.
4. Demonstrate descriptive methods to graphically and numerically summarise the data
5. Apply three separate advanced business analytics techniques (for example; hypothesis tests, probability distributions, regression etc.) can be employed by the business analytics department, to inform organisational decision-making. Students can use actual data if available or simulated data to illustrate the separate techniques.  

Further details:

It is expected that the report will contain charts, graphs, tables etc. as appropriate and will be no longer than 3,000 words in length (excluding any appendices and references).

Additional Information

Students will be penalised if they copy material or re-use the work of others without full acknowledgement (your work must be written in your own words and referenced appropriately).  Please refer to the university’s regulations for more details on plagiarism (http://www.celt.mmu.ac.uk/plagiarism/index.php).

Resources

See Moodle

Group Work Guidelines (If applicable) N/A

Unit Specification

See Moodle

<45%

A weak grasp of the question that demonstrates a considerable misunderstanding in several key areas. Little analysis of the issues is provided.

45-49%

Some evidence of understanding but the work also demonstrates some confusion, misunderstanding and inconsistencies. Overall, the work is insufficient to merit a pass. 

50-59%

A threshold level of understanding demonstrated in terms of the assignment requirements and some attempt to analyse the issues involved. However the work contains some gaps.

60-69%

Students have managed to demonstrate a fairly good understanding of some major issues in the question. However, some of the topics are not always consistently developed. The analysis is satisfactory but is often more descriptive rather than analytical.

70-79%

A good / very good appreciation of the requirements of the question as specified in the assignment brief. The analysis is often good and tends to be more analytical than descriptive.

>85%

An outstanding piece of work where the analysis is highly relevant and the ideas produced demonstrate a high level of critical reflection.