This individual report requires you to use the “CW2_Superstore_data.csv” dataset. Individual report that answers the following tasks up to the specified word count limit. Business Statistics 7034SSL

Student Assignment Brief 

This document is intended for Coventry University Group students for their own use in completing their assessed work for this module. It must not be passed to third parties or posted on any website. If you require this document in an alternative format, please contact your Module Leader.

Contents:

• Assignment Information
• Assignment Task
• Marking and Feedback
• Assessed Module Learning Outcomes
• Assignment Support and Academic Integrity
• Assessment Marking Criteria

The work you submit for this assignment must be your own independent work, or in the case of a group assignment your own groups’ work. More information is available in the ‘Assignment Task’ section of this assignment brief. 

Assignment Information

Module Name: Business Statistics

Module Code: 7034SSL

Assignment Title: Individual Report

Assignment Due: 18:00 UK time

Assignment Credit: 10 credits

Word Count (or equivalent): 2000 words +/- 10%

Assignment Type: Normal CW2

Percentage Grade (Applied Core Assessment). You will be provided with an overall grade between 0% and 100%. You have one opportunity to pass the assignment at or above 40%.

Assignment Task

This individual report requires you to use the “CW2_Superstore_data.csv” dataset.

Individual report that answers the following tasks up to the specified word count limit. In this report, you are required to answer Task 1 to 4 that will start with a Literature Review along with descriptive analysis followed by hypothesis testing, application of testing techniques & its presentation along with a brief conclusion on selected hypothesis.

1.LITERATURE REVIEW

You have been asked to read relevant literature individually and write a review about statistical analysis in published articles on superstores. Your review must be critically discussing the strengths and weaknesses of the statistical approaches and their practical implications to improve the industry/service. You are recommended to review at least five distinct peer-reviewed academic publications published in the last five years (between 2020 and 2024). This literature review will serve you to understand the applicability of business statistics in a particular domain with published research.

For example:

First made a search criterion and identify the potentially relevant literature. You have selected an article based on your search criteria. Now, read the article and write like this 

• Summarise the article in which you need to discuss how this article examines the use of regression models to predict retail sales based on historical sales data and external factors like holidays and promotions.
• Strengths: Regression models provide clear interpretability and are effective for short-term forecasts.
• Weaknesses: They struggle with capturing non-linear relationships and are sensitive to outliers.
  • Practical Implications: Retailers can use regression models to optimise inventory planning but must combine them with robust outlier detection techniques. 

2.DESCRIPTIVE STATISTICS 

Find descriptive statistical measurements and interpret them in a business context. In your interpretation, please assume that you are describing a dataset to a team of professional colleagues who are non-specialists in statistics subject. Data cleaning is an inclusive step. 

For example: You have a raw dataset which may have potential issues, now do the following steps

• Clean the Dataset: Remove irrelevant rows, fix column headers, and format numerical data for analysis.
• Calculate Descriptive Statistics: Compute measures such as mean, median, standard deviation, and range for relevant variables (e.g., "Price per Unit," "Units Sold," "Total Sales").
• Interpretation for Non-Specialists: Present the findings in simple language, focusing on business insights.
• Summarise the key aspects in your own words.

3. HYPOTHESIS TESTING & RESULTS 

Develop Hypothesis/s and critically apply hypothesis testing to examine your cleaned dataset. You can develop hypotheses from your preliminary analysis, wider research and thinking and test these using the data set given above by the statistical techniques listed below at a significance level of 5%.

1. Chi Square Test (X²): Examine relationships between variables to identify potential associations.
2. One-Way ANOVA (including post hoc analysis): Compare means across multiple groups to determine significant differences while identifying specific group variations through post hoc analysis.
3. c.     Multiple Linear Regression (including multicollinearity and VIF analysis): Explore relationships between dependent and independent variables, ensuring the validity of the model by addressing multicollinearity using Variance Inflation Factor (VIF) analysis

For example: Now, suppose you have a cleaned dataset, now do the following steps

• Develop hypotheses based on preliminary analysis and broader research insights.
• Clean and preprocess the dataset to prepare for statistical analysis.
  • Use Chi-Square Test (X²) to identify relationships between categorical variables and assess potential associations.
  • Apply One-Way ANOVA to compare group means and determine significant differences across multiple categories. Conduct post hoc analysis to pinpoint specific group variations.
  • Implement Multiple Linear Regression to examine relationships between dependent and independent variables.
  • Perform multicollinearity analysis using Variance Inflation Factor (VIF) to ensure the regression model’s validity.
  • Test all hypotheses at a 5% significance level and report results with statistical metrics (e.g., p- values, confidence intervals).
  • Interpret findings critically, highlighting patterns, trends, or significant outcomes relevant to the hypothesis.

4.HYPOTHESIS SUITABILITY & CONCLUSION  

Clearly explain why the proposed hypotheses are well-suited for testing using the chosen statistical techniques. Highlight how the techniques align with the type of data. Conclude by summarizing the results and stating your decision regarding the hypotheses, whether they are accepted or rejected,

based on the analysis conducted. Ensure the conclusion is supported by the statistical findings and provide suggestions/advices to the business based on this statistical analysis.

For example: You have made an analysis, now what you need to do is to 

• Justify the suitability of each hypothesis for testing with the selected statistical techniques.
  • Explain how the techniques align with the data type (e.g., categorical for Chi-Square, numerical for ANOVA and regression).
  • Summarize statistical findings clearly, including key metrics such as p-values and confidence intervals.
• State the decision for each hypothesis (accepted or rejected) based on the analysis.
  • Provide actionable business insights derived from the results (e.g., improving inventory management, targeted marketing).
• Offer suggestions for implementing findings to address identified trends or issues effectively.
  • Conclude with a concise summary of the statistical analysis outcomes and their practical implications for the business.

Assignment Guidelines: It is recommended to use Locate or EBSCOhost for your peer reviewed publications literature review. Citations must be in APA format with references listed at the end of the report. It is not advised to use citations other than task (1, and 4). In this individual report, you can use Excel, IBM SPSS, Python, R, Power BI and/or Tableau. Copying code from LLM model is not recommended for tasks. Add graphs with captions where necessary.

Dataset Description: Description of data is as:

• Response (target) - 1 if customer accepted the offer in the last campaign, 0 otherwise
• ID - Unique ID of each customer
  • YearBirth - Age of the customer Complain - 1 if the customer complained in the last 2 years DtCustomer - date of customer`s enrollment with the company
• Education - customer`s level of education
• Marital - customer`s marital status
• Kidhome - number of small children in customer`s household
• Teenhome - number of teenagers in customer`s household
• Income - customer`s yearly household income
• MntFishProducts - the amount spent on fish products in the last 2 years
• MntMeatProducts - the amount spent on meat products in the last 2 years
• MntFruits - the amount spent on fruits products in the last 2 years
• MntSweetProducts - amount spent on sweet products in the last 2 years
• MntWines - the amount spent on wine products in the last 2 years
• MntGoldProds - the amount spent on gold products in the last 2 years
• NumDealsPurchases - number of purchases made with discount
  • NumCatalogPurchases - number of purchases made using catalog (buying goods to be shipped through the mail)
• NumStorePurchases - number of purchases made directly in stores
• NumWebPurchases - number of purchases made through the company`s website
• NumWebVisitsMonth - number of visits to company`s website in the last month
• Recency - number of days since the last purchase

Submission Instructions:

The assessment must be submitted by 18:00 on 10/04/2025. No paper copies are required. Your assignment must be in Microsoft Words format only, NOT in PDF. Avoid uploading from google drive directly as it may convert your assignment into PDF automatically. You can access the submission link through the Aula page – Assignments section.

• Your coursework will be given a zero mark if you do not submit a copy through Turnitin within the assigned time. Please ensure that you have submitted your work properly well before the deadlines. In case of any issue, inform the tutor or the Module Leader well before time via email.
• Please ensure you submitted your work using the correct file format, unreadable files will receive a mark of zero.
• All work submitted after the submission deadline without a valid and approved reason (see below) will be given a mark of zero.
• The University wants you to do your best. However, we know that sometimes events happen which mean that you can’t submit your coursework by the deadline – these events should be beyond your control and not easy to predict. If this happens, you can apply for an extension to your deadline for up to 5 working days, or if you need longer, you can apply for a deferral, which takes you to the next assessment period (for example, to the Resit period following the main Assessment Boards). You must apply before the deadline. You will find information about the process and what is or is not considered to be an event beyond your control at Extenuating Circumstances.
• Students MUST keep a copy and/or an electronic file of their assignment.
  • Checks will be made on your work using anti-plagiarism software and approved plagiarism checking websites.
  • The word count is 2000 words +/- 10%. The word limit includes quotations and citations but excludes the references list.
  • There will be a penalty of a deduction of 10% of the mark (after internal moderation) for work exceeding the word limit by 10% or more. 

Marking and Feedback

How will my assignment be marked?

Your assignment will be marked by the module team.

How will I receive my grades and feedback?

Provisional marks will be released once internally moderated.

Feedback will be provided by the module team alongside grades release.

You will be able to access your feedback via the same Turnitin submission link you submitted your work to.

Your provisional marks and feedback should be available within 10 working days.

What will I be marked against?

Marks distribution as:

Details of the specific CW marking criteria for these tasks can be as 

Generalised details of the marking criteria for this task can be found at the bottom of this assignment brief. 

Assessed Module Learning Outcomes

The Learning Outcomes for this module align to the marking criteria which can be found at the end of this brief. Ensure you understand the marking criteria to ensure successful achievement of the assessment task. The following module learning outcomes are assessed in this task:

Learning Outcomes:

On completion of this module students will be able to:

1. Critically discuss the strengths and weaknesses of a particular statistical approach and the practical implications of a statistical analysis.
2. Evaluate and critically apply appropriate statistical analysis, with the aid of computer packages, to business and management data for business decision-making.
3. Interpret and professionally communicate statistical analysis findings to non-specialists within a business.
4. Make critical judgements on business cases and provide suggestions and advice to the business based on their statistical analysis & finding 

Assignment Support and Academic Integrity

If you have any questions about this assignment, please see the Student Guidance on Coursework for more information.

Spelling, Punctuation, and Grammar:

You are expected to use effective, accurate, and appropriate language within this assessment task. 

Academic Integrity:

The work you submit must be your own, or in the case of groupwork, that of your group. All sources of information need to be acknowledged and attributed; therefore, you must provide references for all sources of information and acknowledge any tools used in the production of your work, including Artificial Intelligence (AI). We use detection software and make routine checks for evidence of academic misconduct. For AI related usage, please refer to the University guidelines

It is your responsibility to keep a record of how your thinking has developed as you progress through to submission. Appropriate evidence could include: version controlled documents, developmental sketchbooks, or journals. This evidence can be called upon if we suspect academic misconduct. If using Artificial Intelligence (AI) tools in the development of your assignment, you must reference which tools you have used and for what purposes you have used them. This information must be acknowledged in your final submission.

Definitions of academic misconduct, including plagiarism, self-plagiarism, and collusion can be found on the Student Portal. All cases of suspected academic misconduct are referred for investigation, the outcomes of which can have profound consequences to your studies. For more information on academic integrity please visit the Academic and Research Integrity section of the Student Portal.

Support for Students with Disabilities or Additional Needs:

If you have a disability, long-term health condition, specific learning difference, mental health diagnosis or symptoms and have discussed your support needs with health and wellbeing you may be able to access support that will help with your studies.

If you feel you may benefit from additional support, but have not disclosed a disability to the University, or have disclosed but are yet to discuss your support needs it is important to let us know so we can provide the right support for your circumstances. Visit the Student Portal to find out more.

Unable to Submit on Time?

The University wants you to do your best. However, we know that sometimes events happen which mean that you cannot submit your assessment by the deadline or sit a scheduled exam. If you think this might be the case, guidance on understanding what counts as an extenuating circumstance, and how to apply is available on the Student Portal.

This document is intended for Coventry University Group students for their own use in completing

Administration of Assessment

Module Leader Name: 

Module Leader Email: 

This document is intended for Coventry University Group students for their own use in completing

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Assessment Marking Criteria

Guidance for Course Teams: Assessment criteria should align to the University-level assessment criteria for the relevant level of study. These are available through the Academic Enhancement and Professional Development website. Training on assessment and feedback approaches is available through the Course Booking System.

(Delete if not applicable or replace with different marking criteria)

Important: If the assessment used is a Core (Pass/Fail) assessment then please amend the marking criteria accordingly. Guidance on the use of Core Assessment is available on the Office of Teaching and Learning SharePoint site.