NMIMS Solved Assignment Business Analytics December 2025

NMIMS Solved Assignment Business Analytics Dec 2025 :  [Unique]
NMIMS Solved Assignment Business Analytics Dec 2025 :

Assignment Marks: 20
Instructions
PLEASE NOTE: This assignment is application based, you have to apply what you have
learnt in this subject into real life scenario. You will find most of the information through
internet search and the remaining from your common sense. None of the answers appear
directly in the textbook chapters but are based on the content in the chapter

NMIMS Centre for Distance and Online Education (NCDOE)
Course: Business Analytics
Internal Assignment Applicable for Dec 2025 Examination
Q1 A retail chain is preparing to launch a new analytics dashboard to monitor sales
performance. While compiling the sales dataset, the analyst notices that several
entries in the ‘delivery amount’ column are missing due to data entry errors and
system glitches. The dataset will be used to generate visualisations for management
decision-making. The analyst must select and apply the most suitable imputation
method to fill in the missing values, ensuring that the resulting analysis accurately
reflects business performance and is not skewed by the chosen technique. Given the
scenario, how should the business analyst apply appropriate imputation methods to
handle missing delivery amounts in the sales dataset, and what considerations should
guide the choice between mean, median, and mode imputation for this retail context?
(10 Marks)
Q2 (A) After applying statistical inference, Mehta E-Commerce identified several
factors—such as product quality, delivery speed, and customer support—that
significantly impact customer satisfaction. The company must now decide how to
allocate resources to address these areas, considering limited budgets and competing
business objectives. Assess the strategic implications of resource allocation decisions
made by Mehta E-Commerce after identifying statistically significant factors
affecting customer satisfaction. How should management weigh the statistical
significance of these factors against business priorities, operational constraints, and
potential unintended consequences when justifying investments in improvement
initiatives?
(5 Marks)
Q2 (B) A retail company has implemented a simple linear regression model to forecast
monthly sales based on advertising spend. The analytics team reports a high Rsquared
value, leading management to believe the model is highly reliable. However,
some team members question whether R-squared alone provides a complete picture of
model performance, especially given the complexity of market dynamics and the risk
of overfitting. Assess the effectiveness of using the coefficient of determination (Rsquared)
as the primary metric for evaluating the fit of a simple linear regression
model in a business context. What are the potential pitfalls of over-relying on Rsquared,
and how would you recommend balancing it with other diagnostic tools to
ensure robust model assessment?
(5 Marks)