Assessment instructions for students (as per QMPlus ‘Assessment Information’ tab)
1. Assessment information
This assignment is designed to assess learning outcomes:
A2: Apply and effectively interpret the results of statistical analysis methods in business and management research
A3: Design and execute a data analysis exercise using appropriate sources
B2: Develop numeracy and quantitative skills in data analysis, interpretation and extrapolation
B3: Demonstrate the ability to conduct research involving business and management data either individually or as part of a team.
C2: Use statistical software and other technologies to access, interpret, critically evaluate and visualise data from multiple sources
C4: Develop a strong sense of research ethics and intellectual integrity involving the use of data
2. Instructions and guidance
This assignment is an individual assignment. Case study:
Background:
TechGlobal Corp, an established IT company, has been actively investing in technology over the last 20 years to drive innovation and maintain its competitive edge. With the launch of generative AI (GenAI) platforms in November 2021, TechGlobal Corp decided to intensify its focus on AI technologies, recognising the potential for significant enhancements in operational efficiency and market responsiveness.
Objectives:
- Evaluate the impact of intensified AI investments on key business metrics such as sales, profits, staff satisfaction, customer satisfaction and employee turnover.
- Analyse the shifts in business performance pre and post the adoption of technologies such as GenAI.
- Provide strategic recommendations based on the analysis of historical data and technology investmentoutcomes.Data Description:
- Period: 2001 – 2021 (Pre-GenAI era) and 2021 – 2023 (Post-GenAI era)
- Variables: Sales, Profits, Investment in Technology (with a specific focus on AI post-November 2021),Staff Satisfaction, Employee Turnover, and Customer Satisfaction.
- Frequency: Seasonal data points (4 data points per year) for each variable, resulting in a total of 92data points per variable.
- Total Data Points: 6 variables x 92 data points = 552 data points.Your tasks:
1) Choose a single variable to focus on for forecasting analysis.
- 2) Determine relevant variables, formulate 2-3 hypotheses, perform tests on these hypotheses, and explain the outcomes.
- 3) Provide a well-founded recommendation based on the analysis of the data.
- 4) Reflect on the effectiveness and accuracy of AI tools were utilised for analysing and interpreting thedata.
Please Note: The Excel file, containing the forecasting calculations and hypothesis testing, must be submitted together with the coursework. Failure to submit the Excel file will result in a 10% deduction from your total marks.
3. Structure
Your assignment should be presented using the following structure:
Section
2. Methodology
4. Hypotheses Development
6. Results and Discussion
7. Conclusion and Recommendations
8. AI Tools Reflection
9. References 10. Appendices
4. Criteria for Assessment
Marks will be allocated as follows:
Coursework element
Clear formulation and reasoning for hypotheses development
Accuracy in forecasting calculations
Accuracy in hypotheses testing
Depth of interpretation and discussion of results, and solid recommendation. Insightfulness of reflection on the use of AI tools.
Total
Content Coverage
– Description of data sources
– Details of AI tools and software used for analysis
– Overview of forecasting techniques and hypothesis testing methods
– Detailed formulation of each hypothesis – Rationale for the chosen hypotheses
– Comprehensive analysis of findings
– Comparison of results against hypotheses
– Discussion on the impact and implications of findings
– Summary of key findings
– Conclusions drawn from the analysis
– Recommendations based on study outcomes
– Critical assessment of AI tools used in the study
– Discussion on the effectiveness and limitations of AI tools in data analysis and data interpretation
– Comprehensive list of all academic sources and data sources cited in the study
– Additional data, charts, or details relevant to the study but not included in the main text
1. Introduction
– Overview of the study’s objectives
– Overview of data sources utilised
– Explanation of the selected variables
3. Forecasting Analysis
– Detail the forecasting models used
– Choose one of the variables and conduct forecasting analysis in the Excel.
– Interpret the data
– Present the prompts used for forecasting in GenAI
– Compare results from Excel and GenAI tools
5. Hypothesis Testing
– Test each hypothesis in the Excel
– Show test results and their statistical significance
– Present the prompts used for hypothesis testing in GenAI – Compare results from Excel and GenAI tools
Mark split
10% 25% 25% 30% 10% 100%
5. Word Count
The word count is 2000. 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.
Tables, diagrams, appendices and references are omitted from the overall word count. Sections contributing to the word count are indicated. You may also include tables, diagrams and models. Ensure that all tables, diagrams and models are labelled, include a citation and are discussed in the text. Appendices and reference list are not included in the word count.