MMPC-005 : QUANTITATIVE ANALYSIS FOR MANAGERIAL APPLICATIONS (June 2025 Question Paper)

 No. of Printed Pages : 5 MMPC–005

MANAGEMENT PROGRAMME (MP)

Term-End Examination

June, 2025

MMPC-005 : QUANTITATIVE ANALYSIS FOR MANAGERIAL APPLICATIONS

Time : 3 Hours Maximum Marks : 100

Note : Answer any five questions. All questions carry equal marks. Calculators are allowed.

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1.

Explain the concept of random variable and probability distribution. Elucidate the usefulness of probability distribution in decision-making.

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2.

Consider the following grouped data which relate to the profits of 100 companies:

Profit (in ₹ lakhs)	No. of Companies
20–30	4
30–40	8
40–50	18
50–60	30
60–70	15
70–80	10
80–90	8
90–100	7

Calculate Q₂ and D₆ and interpret these values.

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3.

Give various reasons which make sampling a desirable, and in many cases, the only course open for making an inference about a population.

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4.

If the probability is 0.30 that a Management Accountant’s job applicant has a post-graduate degree, 0.70 that he had some work experience as a Chief Financial Accountant, and 0.20 that he has both, out of 300 applicants, approximately what number would have either a post-graduate degree or some professional work experience?

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5.

What procedure do you follow while testing for difference between proportions? State the null and alternative hypotheses. What is the use of the pooled estimate of p?

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6.

A company that manufactures batteries guarantees them a life of 24 months.

(i) If the average life has been found in tests to be 33 months and a standard deviation of 4 months, how many will have to be replaced under guarantee if a normal distribution is assumed for battery lifetimes?

(ii) If annual sales are 10,000 batteries at a profit of ₹50 each and each replacement costs the company ₹100, find the net profit.

(Given Z value corresponding to the area between X = 24 and X̄ = 33 is 0.4878.)

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7.

Write short notes on any three of the following:

(a) Discrete and Continuous Data

(b) Relative Skewness

(c) Cluster vs. Stratum

(d) Type I and Type II Errors

(e) Least Square Criterion

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