DBB2108 QUANTITATIVE TECHNIQUES FOR MANAGEMENT JULY – AUGUST 2025

Description

SESSION	JULY – AUGUST 2025
PROGRAM	BACHELOR OF BUSINESS ADMINISTRATION (BBA)
SEMESTER	III
COURSE CODE & NAME	DBB2108 QUANTITATIVE TECHNIQUES FOR MANAGEMENT

 

 

Set-I

 

 

Q1. Elaborate the characteristics of Statistics.

Ans 1.

Characteristics of Statistics

Statistics is a discipline that deals with the scientific collection, organisation, presentation, analysis, and interpretation of data. It transforms raw figures into meaningful information that supports decision-making. In management, economics, psychology, and social sciences, statistics plays an essential role because it helps understand patterns, measure performance, and predict future trends. The characteristics of statistics highlight its importance and explain why it is used

 

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Q2. Explain the methods of mean, median and mode for frequency data.

Ans 2.

Methods of Mean, Median, and Mode for Frequency Data

Measures of central tendency provide a single value that represents an entire dataset. In frequency data, values occur repeatedly, making it important to identify a central position around which the data is concentrated. Mean, median, and mode are the three most widely used measures. Though each measure serves the same purpose, their methods and interpretations differ significantly. Understanding them helps managers analyse data and make informed decisions.

Mean for Frequency Data

The mean is considered the most common measure of central tendency because it takes every

 

Q3. The values of X and Y are given below:

X	1	3	5	7	9
Y	9	7	5	3	1

 

Calculate the correlation coefficient between X and Y.

Ans 3.

Correlation Coefficient between X and Y

Given:

X	1	3	5	7	9
Y	9	7	5	3	1

 

Here X increases, Y decreases perfectly in a straight-line pattern.

Let’s compute using the Pearson correlation formula:

We observe that:

• When X = 1, Y = 9
• When X = 3, Y = 7
• When X = 5, Y = 5
• When X = 7, Y = 3
• When X = 9, Y = 1

 

Set-II

 

Q4. Calculate the five-year moving average of the following data:

Year	1950	1951	1952	1953	1954	1955	1956
Values	105	115	100	90	80	95	85

 

Ans 4.

Five-Year Moving Average

Data:

Year	1950	1951	1952	1953	1954	1955	1956
Value	105	115	100	90	80	95	85

 

Calculate 5-year moving averages.

A 5-year moving average means we take 5 consecutive years at a time, find their average, and “move” one year forward each time.

1st 5-year moving average (for 1950–1954)

Years = 1950, 1951, 1952, 1953, 1954

 

 

 

Q5. What is acceptance sampling? Discuss the concept of OC curve. 10

Ans 5.

Acceptance Sampling and the Concept of OC Curve

Acceptance sampling is a statistical quality-control technique used to decide whether a batch of products (known as a lot) should be accepted or rejected based on the inspection of a small sample taken from the lot. Instead of checking every item—which may be costly, time-consuming, or destructive—acceptance sampling allows organisations to evaluate quality by examining only a portion. This method is widely used in manufacturing, pharmaceuticals, packaging, electronics, and defence industries where inspection of the entire lot is not practical.

Meaning of Acceptance Sampling

In acceptance sampling, a predetermined number of units are selected randomly from a lot and inspected for defects. Based on the number of defective items found in the sample, the decision is made to accept or reject the entire lot. The sampling plan specifies two key elements: the sample size and the acceptance number, which indicates how many defective items are allowed in the sample. The essence of acceptance sampling lies in balancing the cost of inspection with the risk of passing defective goods to the customer.

Acceptance sampling does not guarantee perfect quality; rather, it controls the probability that lots of unacceptable quality will be accepted. It is, therefore, a risk-based decision tool used to

 

Q6. Define independence of attributes. State the mathematical condition and explain with an example. 10  

Ans 6.

Independence of Attributes – Meaning, Condition, and Example

In statistics, the study of attributes involves analysing qualitative characteristics such as gender, preference, behaviour, taste, or defect type. When two attributes are considered, it becomes important to determine whether they influence each other or whether they occur independently. Independence of attributes is a fundamental concept in classification, probability theory, and research analysis, helping managers and researchers understand relationships between variables.

Meaning of Independence of Attributes

Two attributes are said to be independent if the presence or absence of one attribute has no effect