LUBS5996M Understanding Data for Decision Making Resit ACW Auguest 2024/2025

Published: 18 Aug, 2025

Category	Assignment	Subject	Business
University	University of Leeds	Module Title	LUBS5996M Understanding Data for Decision Making

Assessment Type	Coursework
Assessment Title	3,000 words

LUBS5996M Assignment:

This assignment has been designed to enable you to evidence your ability to prepare, understand, and analyse data for informed decision making in a managerial capacity. The coursework will be assessed against the criteria mentioned at the end of this brief.
Imagine that you are working for a consultancy firm, called Vision, which is working on a project related to effective use of UK police force. You are asked to provide insights into severity, frequency and types of crimes happening around the UK. Based on these insights, you are asked to prepare recommendations for policy makers on how much they should be spending on policing crime.

The big question to investigate is:

How would you distribute £20 billion for policing in the UK?
You are provided with an open dataset containing information on crimes in the UK. You can access their data on data police uk/data/ which covers past crime incidents. It is your choice to see how deep you want to investigate it, however, as a guidance, investigate at least for the last three years.
As a part of this assessment, it is expected that students will also identify other data sources that can help improve the decision-making process. To answer this big question, you must demonstrate your skills in the following areas:
Data Understanding: Inspect the data provided with the case study. To demonstrate your critical thinking, identify and suggest additional sources of data that are not provided but can help investigate this big question.
Data Preparation: Perform operations like filtering, sorting, transformation, and enrichment to make data more useful and information-rich before analysing them.
Exploratory Analysis: Calculate basic statistics, create visualisations (charts, graphs) to represent key trends, seasonal variations, and to identify any outliers.
Managerial Insights: Provide insights derived from your analysis. For example, structured analysis of each county and each type of crime; and comparing different areas for their liveability.
Recommendations: Formulate actionable recommendations for distributing moneys to each region (and/or types of crime).

You MAY use GenAI (if you wish) for help with the elements of searching and reading the literature, and improving your expression in English. These tasks are necessary to complete the assignment, but are not specifically part of the marking. Past students have noted that the extensive reading and/or complex expression, is onerous for some people but easier for others. If you would find it helpful, you may use GenAI to (1) summarise research papers, enabling you to target your full-length reading to the most relevant ones, and (2) tidy up your English, after you have written the content [for example, write it in your own voice and then ask Co-Pilot to render it into a more academic tone, or, ask it to check the grammar/spelling]. Note you may NOT ask Co-Pilot to create content or write things for you, or for anything other than the two tasks specified above. Also remember that you retain responsibility for what you hand in; Co-Pilot is susceptible to errors and biases, so always check over anything that you’ve used GenAI on.
Finally, please note that these instructions are particular to this assignment. Other assignments will have different instructions for which parts you may and may not use GenAI for. Not all Amber assignments will be the same.

All coursework assignments that contribute to the assessment of a module are subject to a word limit, as specified on the assessment brief. The word limit is an extremely important aspect of good academic practice and must be adhered to. Unless stated otherwise in the relevant module handbook (if one has been provided), the word count includes EVERYTHING (i.e. all text in the main body of the assignment including summaries, subtitles, contents pages, tables, supportive material whether in footnotes or in-text references) except the main title, reference list and/or bibliography and any appendices. It is not acceptable to present matters of substance, which should be included in the main body of the text, in the appendices (“appendix abuse”). It is not acceptable to attempt to hide words in graphs and diagrams; only text which is strictly necessary should be included in graphs and diagrams.

You are required to adhere to the word limit specified and state an accurate word count on the cover page of your assignment brief. Your declared word count must be accurate, and should not mislead. Making a fraudulent statement concerning the work submitted for assessment could be considered academic malpractice and investigated as such. If the amount of work submitted is higher than that specified by the word limit or that declared on your word count, this may be reflected in the mark awarded and noted through individual feedback given to you.

The deadline date for this assignment is 12:00:00 noon on Thursday 14th August 2025.

An electronic copy of the assignment must be submitted to the Assignment Submission area within the module resource on the Blackboard MINERVA website no later than 12:00:00 noon prompt on the deadline date.

Emailed copies of the assignment will not be accepted.

Failure to meet this initial deadline will result in a reduction of marks, details of which can be found at the following place:
LUBS Student Guide/assessment/code-of-practice-on-assessment/

MITIGATING CIRCUMSTANCES

If you are affected by circumstances that will have a short-term impact on your ability to complete coursework assessments (for example a minor illness), you can make an application for an extension to a coursework deadline. Please note, all extension requests must be made prior to the original assessment deadline.

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SUBMISSION

Please ensure that you leave sufficient time to complete the online submission process, as upload times can vary. Accessing the submission link before the deadline does NOT constitute completion of submission. You MUST click the ‘CONFIRM’ button before 12:00:00 noon for your assignment to be classed as submitted on time, if not your assignment will be marked as late. It is your responsibility to ensure you upload the correct file to the MINERVA, and that it has uploaded successfully.

It is important that any file submitted follows the conventions stated below:

FILE NAME

The name of the file that you upload must be your student ID only.

ASSIGNMENT TITLE

During the submission process the system will ask you to enter the title of your submission. This should also be your student ID only.

FRONT COVER

The first page of your assignment should always be the Assessed Coursework Coversheet (individual), which is available to download from the following location:

LUBS Student Guide/forms-guidance-and-coversheets/

STUDENT NAME

You should NOT include your name anywhere on your assignment

LUBS5996M Module-specific criteria (rubric)

	Distinction	Merit	Pass	Fail
Data Understanding	Demonstrates a profound understanding of the dataset, including its sources, variables, limitations, and relevance to the business problem. Exhibits a sophisticated grasp of statistical concepts and methods relevant to the analysis.	Shows a comprehensive understanding of the dataset, including key variables and sources. Demonstrates proficiency in relevant statistical concepts and methods.	Shows a basic understanding of the dataset, including some key variables and sources. Demonstrates basic proficiency in relevant statistical concepts and methods.	Demonstrates a lack of understanding of the dataset and its relevance to the business problem. Shows minimal proficiency in statistical concepts and methods.
Data Preparation	Effectively cleanses and prepares the dataset, addressing missing values, outliers, and inconsistencies with precision and clarity. Utilizes advanced techniques to enhance data quality and integrity.	Demonstrates proficient data cleaning and preparation techniques, effectively addressing most missing values, outliers, and inconsistencies.	Demonstrates basic data cleaning and preparation techniques, addressing some missing values, outliers, and inconsistencies.	Demonstrates inadequate data cleaning and preparation techniques, leaving significant missing values, outliers, and inconsistencies unaddressed.
Exploratory Analysis	Conducts a comprehensive and insightful exploratory analysis, employing advanced statistical and visualization techniques to uncover patterns, trends, and relationships within the data.	Conducts a thorough exploratory analysis, utilizing appropriate statistical and visualization techniques to identify key insights within the data.	Conducts a basic exploratory analysis, utilizing standard statistical and visualization techniques to identify some insights within the data.	Conducts a superficial exploratory analysis, failing to identify meaningful insights within the data.
Managerial Insights	Demonstrates a sophisticated understanding of managerial analysis, effectively integrating data insights with strategic business objectives. Provides nuanced interpretations and implications of the analysis for decision making.	Provides a comprehensive managerial analysis, integrating data insights with business objectives. Offers clear interpretations and implications of the analysis for decision making.	Provides a basic managerial analysis, linking data insights with business objectives. Offers some interpretations and implications of the analysis for decision making.	Provides an incomplete or superficial managerial analysis, failing to effectively link data insights with business objectives.
Recommendations	Offers insightful and actionable recommendations based on the analysis, demonstrating a deep understanding of the business context and implications of the data-driven insights.	Provides clear and relevant recommendations based on the analysis, demonstrating an understanding of the business context and implications of the data-driven insights.	Provides basic recommendations based on the analysis, demonstrating some understanding of the business context and implications of the data-driven insights.	Provides inadequate or irrelevant recommendations based on the analysis, failing to demonstrate an understanding of the business context and implications of the data-driven insights.

	Understanding	Research and evidence	Analysis and Evaluation	Presentation
+ 80	Exceptional knowledge of key foundational principles and concepts; ability to evaluate and interpret these innovatively within the area of study. Awareness of ambiguities of knowledge	Exceptionally wide range of appropriate research-informed reading beyond the taught elements of the module; ability to decipher relevant data/information/sources to address question/investigation	Exceptional ability to identify and apply relevant techniques to present, evaluate and interpret quantitative and/or qualitative data in accordance with foundational theories; sophisticated interpretation of key arguments and identification of points of difference in literature	Exceptionally coherent, clear, balanced and persuasive argument; strong focus on relevant issues; use of logical structure including clear, valid and reflective conclusions; accurate and consistent citation and referencing
79 to 70	Excellent knowledge of key foundational principles and concepts; ability to evaluate and interpret these reflectively within the area of study. Begins to show awareness of limitations to knowledge	Very high quality evidence of appropriate research-informed reading beyond the taught elements of the module; ability to engage with relevant data/information/sources to address question/investigation	Excellent ability to identify and apply relevant techniques to present, evaluate and interpret quantitative and/or qualitative data in accordance with foundational theories; clearly identifies relevant arguments and points of difference in literature	Very high quality, coherent, clear, balanced and persuasive argument; strong focus on relevant issues; use of logical structure including clear, valid and reflective conclusions; accurate and consistent citation and referencing
69 to 60	Good knowledge of foundational principles and concepts; ability to evaluate and interpret these within the area of study	High quality evidence of appropriate research-informed reading beyond the taught elements of the module; ability to locate required data/information/sources to address question/investigation	Good ability to apply required techniques to present, evaluate and interpret quantitative and/or qualitative data in accordance with foundational theories; identifies key arguments and points of difference in literature	High quality, coherent, clear and balanced argument; strong focus on relevant issues; use of logical structure including clear and valid conclusions; accurate and consistent citation and referencing
59 to 51	Reasonable knowledge of foundational principles and concepts; shows some ability to evaluate and interpret these within the area of study; some errors may be evident	Evidence of appropriate reading within the taught elements of the module; competent ability to locate data/information/sources to address question/investigation	Competency in applying required techniques to present, evaluate and interpret quantitative and/or qualitative data in accordance with foundational theories; identifies arguments and points of difference in literature but often descriptively	Reasonable, clear argument; focus on relevant issues; appropriate structure with good conclusion; accurate and consistent citation and referencing
50	Threshold level Adequate knowledge of foundational principles and concepts; shows limited ability to evaluate and interpret these within the area of study; some errors and omissions evident	Threshold level Use of set reading only; limited ability to locate data/information/sources to address question/investigation	Threshold level Limited ability to apply some techniques to present, evaluate and interpret quantitative and/or qualitative data in accordance with foundational theories	Threshold level Limited argument; reasonable focus; structure evident; evidence of largely correct referencing and citation
49 to 30	Work does not meet the standards required to pass; gaps in knowledge of foundational principles and concepts; superficial attempts to evaluate or interpret these	Little evidence of reading within the taught elements of the module; insufficient ability to locate data/information/sources to address question/investigation	Lacking in ability to apply techniques to present, evaluate and interpret quantitative and/or qualitative data; little understanding of arguments and points of difference in literature	Work does not meet the standards required to pass; unstructured argument; lacking in focus; severe weaknesses in referencing and citation
29 to 1	Work is well below the standards required to pass; major gaps in knowledge of foundational principles and concepts; lacks evaluation and interpretation	No evidence of reading; unable to locate data/information/sources	No techniques used to present, evaluate and interpret data; no understanding of arguments and literature	Work is well below the standards required to pass; lacks argument; no focus; no referencing
0	Work of no merit or absent

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