Quantitative Methods – I DEC 2025

Description

Quantitative Methods – I

Dec 2025 Examination

 

 

Q1. A telecommunications company is piloting a new internet service and surveys 250 randomly selected customers, finding that 162 express interest in subscribing. The marketing analyst is required to estimate, with 90% confidence, the proportion of the entire customer base likely to be interested in the new service. The analyst must apply the correct estimation approach for proportions and ensure the results are suitable for strategic decision-making. In this scenario, how should the marketing analyst apply the interval estimation formula for proportions to determine the confidence interval for the proportion of customers interested in a new service? Explain your reasoning and the steps involved. (10 Marks)

Ans 1.

Introduction

When a company is planning to launch a new product or service, estimating customer demand becomes an essential part of strategic decision-making. In the given case, a telecommunications company surveyed a sample of its customers to understand the level of interest in a new internet service. Since it is not possible to ask every customer in the entire population, the marketing analyst uses the method of interval estimation to infer the likely proportion of interested customers in the broader market. Interval estimation provides a range of values rather than a single point estimate, which allows for a more realistic understanding of uncertainty. By applying a confidence interval for proportions, the analyst can present reliable evidence to

Its Sample only

Get fully solved assignments now

NMIMS DEC 2025 Complete Assignments Available!

Price: Just ₹150/- per assignment

Last date 16 Oct 2025

Expert Writers – Trusted by 1000+ Students

For unique and plagiarism free  Assignment please contact us

WhatsApp: +91 98973 11990

Mail us- : Assignment247team@gmail.com

Buy cheap assignment help online — Easy, Fast, Reliable!

Our website – https://nmimsassignments.in/

buy-online – https://nmimsassignments.in/buy-online/

 

Q2(A). A financial advisory firm tracks client satisfaction rates for three advisors. Initially, the firm uses prior probabilities based on the number of clients per advisor. After a client reports high satisfaction, the firm wants to update the probability that this client was served by each advisor using Bayes’ theorem. The management is debating whether this approach will yield actionable insights for performance evaluation and resource allocation. Assess the appropriateness of applying Bayes’ theorem to revise probabilities in a financial advisory firm where new information about client satisfaction becomes available. What factors should the firm consider to ensure the revised probabilities are meaningful and actionable? Critically justify your evaluation. (5 Marks)

Ans 2a.

Introduction

When new evidence arrives, leaders want probabilities that reflect it. In a financial advisory firm, management begins with prior probabilities for which advisor served a client, based on each advisor’s client share. After a client reports high satisfaction, Bayes’ theorem offers a principled way to update those priors using each advisor’s observed high-satisfaction rates. Done well, this yields sharper attribution and supports targeted coaching, incentives, and scheduling. Done

 

 

Q2(B). A large financial institution is standardizing its risk analysis procedures. Some departments use Excel’s NORM.DIST and NORM.INV functions for normal distribution calculations, while others rely on the traditional z-table. Management is concerned about consistency, accuracy, and the ease of training new analysts. The institution must decide which method to adopt as the standard for all probability calculations. Assess the implications of using Excel’s NORM.DIST and NORM.INV functions versus the traditional z-table for probability calculations in a large financial institution. How should the institution weigh the trade-offs between computational efficiency, accuracy, and interpretability when standardizing probability analysis  across departments? (5 Marks)

Ans 2b.

Introduction

A large financial institution needs consistent, auditable probability work. Different teams currently use either spreadsheet functions or printed tables to compute normal probabilities and quantiles. The choice affects speed, accuracy, training, and controls. While z-tables build intuition, they introduce interpolation and transcription errors. Spreadsheet functions are faster and more precise but can become opaque or misused without standards. The right policy should