Reference no: EM134014685

Foundation Skills in Data Analysis

Learning Outcome 1: Apply the fundamentals of Analytics to solve real world problems
Learning Outcome 2: Manipulate and summarise data that accurately represents real world problems
Learning Outcome 3: Interpret and appraise statistical output to assist in real-world decision making

Assignment

Description

Purpose

This task requires students to apply the ideas and concepts introduced in Modules 1, 2 and 3 to analyse business datasets and communicate evidence-driven insights in a structured report. By completing this assignment, you will develop the ability to apply descriptive statistics, inferential statistical methods, regression analysis, time series analysis and forecasting methods and related quantitative techniques to address real-world organisational challenges (GLO1, ULO1). You will also strengthen competencies in manipulating and summarising datasets accurately (GLO4, ULO2), and rigorous interpretation and critical evaluation of analytical outputs to inform business decision-making (GLO4, ULO3). This assignment further advances your data literacy and professional communication capabilities, enabling you to translate complex statistical outputs into fair, neutral, transparent, and actionable evidence-based insights. In doing so, it prepares you to present actionable conclusions/recommendations that support strategic planning, enhance operational decision-making, and guide stakeholders with analytical rigor, integrity, and clarity.

Context/Scenario

GlobalVision Analytics is a fictitious international socio-economic consultancy firm that has operated for over 20 years, providing evidence-driven insights into global development trends. While the firm maintains several regional hubs in major global markets to handle localised data collection, its primary Strategic Intelligence Department is centralised at the London Head Office. This department is responsible for high-level research that informs international policy, investment strategies, and the firm's overarching corporate direction. The executive team requires a multi-layered analysis that bridges the gap between social wellbeing and macroeconomic performance. Specifically, the project involves:

Social Impact Analysis: Developing a robust predictive model for the Happiness Index to understand the factors driving national stability and quality of life.
Macro-Economic Forecasting: Analysing the USA Annual GDP per Capita (USD) to serve as a primary macro-level demand signal for GlobalVision's international investment volume and consultancy demand.
Regional Market Sensitivity: Evaluating Quarterly Household Spending in Australia to identify seasonal consumer patterns, allowing the firm to better align its regional resources and advisory services with market fluctuations.
Macro-Economic Indexing: Converting raw USA GDP data into a standardised GDP Index to serve as a performance benchmark. This enables GlobalVision to analyse how absolute changes in national wealth influence long-term supermarket and consultancy sales revenue, as well as global investment volume.

Complete the following tasks using the GlobalDataA3 Dataset.

Task 1: Happiness Index Predictive Model

As the 2026 strategic planning cycle approaches, GlobalVision Analytics requires a robust understanding of the variables driving national wellbeing. Significant variability has been observed in the Happiness Index (0-10) across different countries. Your task is to develop a robust predictive model that can support management in predicting national happiness levels. In completing this task, you are expected to:

Identify and justify the selection of appropriate predictor variables.

Which three independent variables have the strongest linear relationship with the Happiness Index?
Which independent variable(s) have a non-linear relationship with the Happiness Index?
Are there any potential multi-collinearity problems? If so, which variables are they?
Select an appropriate modelling approach to predict national happiness levels, clearly explain its key components, and justify its suitability in the context of the dataset and the objective of Task 1.
Estimate the regression equation, interpret its coefficients, and then assess its performance using relevant statistical or analytical metrics, and interpret the results in a global and policy context.
Discuss the underlying assumptions of your estimated regression equation. Furthermore, identify potential limitations of the model, and evaluate how these might impact the reliability of your happiness predictions.
Based on your findings, provide actionable insights for management.

Task 2.1: Annual GDP per Capita (USD), USA

GlobalVision Analytics leadership seeks to enhance its long-term strategic planning by better understanding how the United States' national economic productivity influences the global demand for high-level consultancy and advisory services. While the firm tracks its own internal project volumes, the USA Annual GDP per Capita (USD) is considered a primary macro-level demand signal that shapes the firm's international investment strategies and budgeting decisions. The finance team believes that sustained levels of national productivity correlate with the firm's ability to secure large-scale global contracts, and they require a formal predictive analysis to prepare for the 2027 financial year.

Construct and interpret the time series plot of the USA Annual GDP per Capita (USD).
Select and provide a professional justification for one simple forecasting model and one more complex forecasting model, then fit both models to the historical GDP dataset.
Perform a residual analysis to evaluate if the assumptions of your selected models are valid and calculate standard forecast accuracy metrics to determine the reliability of the models.
Use the analytical evidence generated to compare the simple and complex forecasting models, selecting the most appropriate model for GlobalVision's long-term outlook while fully explaining your reasoning.
GlobalVision recorded $2.6 billion in global investment volume for the year 2026. Using the USA Annual GDP per Capita (USD) as your macro-level demand indicator, forecast the expected investment volume for the year 2027.

Task 2.2: Monthly Household Spending $ Millions, Australia

GlobalVision Analytics recognises that its broader business performance is heavily influenced by patterns in consumer behavior. By accurately forecasting Quarterly Household Spending in Australia, the firm can anticipate seasonal demand shifts and more effectively plan its global resource allocation and advisory services. This foresight allows GlobalVision to manage fluctuations in client demand throughout the year, ensuring a competitive advantage in the international market.

Construct and interpret the time series plot of Australian Quarterly Household Spending.
Develop a forecasting equation suitable for seasonal data, clearly explain its key components, and interpret its coefficients.
Plot the forecast alongside the historical spending data.
Comment on the adequacy of the fitted model by interpreting the analytical output, including residual analysis and forecast error metrics.
Forecast quarterly Australian Household Spending for the next three periods i.e. April, July and October quarters of 2027.

Task 2.3: Annual GDP per Capita (USD), USA

GlobalVision intends to further explore how US national productivity relates to its international supermarket and consultancy sales revenue. To facilitate this, the finance team plans to convert the raw annual GDP values into a standardised GDP Index. Your task is to construct this index, which will serve as a benchmark to analyse how absolute changes in national wealth influence GlobalVision's long-term sales performance.

Construct an index for the USA Annual GDP per Capita (USD) by selecting an appropriate base year.
Provide justification explaining why the selected base year is suitable for the construction of this index.
Discuss how variations in the GDP Index, relative to your selected base year, may influence GlobalVision's supermarket sales revenue and global investment volume.

Specific Requirements

Before attempting the assignment, make sure you have prepared yourself well. At a minimum, please read the relevant sections of the prescribed textbook and review the materials provided in Modules 1, 2 and 3.