BBA/B.COM Business Statistics for Decision Making Dec 2025

Description

Business Statistics for Decision Making

Dec 2025 Examination

 

 

Q1. Given the following paired data on advertising expenditure (Rs. in lakhs) and corresponding sales revenue (Rs. in lakhs) for eight regions:

Advertising    (Rs. lakhs)	5	7	8	6	10	12	9	11
Sales (Rs. lakhs)	15	17	20	16	25	27	22	24

 

Calculate the Pearson correlation coefficient.

Interpret the result in the context of the relationship between advertising and sales performance. (10 Marks)

Ans 1.

Introduction

Business organizations regularly spend on advertising with the expectation that such investment will directly influence sales revenue. To evaluate the strength and nature of this relationship, statistical tools are applied that measure how two variables move together. One of the most common and useful techniques is the Pearson correlation coefficient, which quantifies the linear association between two sets of data. A positive coefficient shows that as one variable increases, the other also rises, while a negative value shows an opposite relationship. In this case, we analyze the data of advertising expenditure and sales revenue for eight

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Q2(A). A company calculates the mean monthly income of its employees to be Rs.42,000. However, some managers argue that the median would be a more appropriate measure of central tendency for salary data. Critically evaluate this claim by discussing the conditions under which the mean or median is a better measure. Support your evaluation with statistical reasoning and possible real-life implications for salary reporting. (5 Marks)

Ans 2a.

Introduction

When a company calculates the average monthly income of employees, the result is often used to summarize the financial standing of its workforce. In this case, the mean salary is reported as Rs.42,000. However, managers argue that the median would better represent the actual situation. The debate arises because salaries usually vary widely, with a few employees earning exceptionally high incomes. It is therefore important to evaluate under what conditions the mean

 

 

Q2(B). In reviewing sales data for home appliances, ABC Electronics’ analysts found that the West region’s sales distribution is highly positively skewed, with a long right tail indicating a few very high sales but most stores performing below average. Management is debating how to interpret this skewness and what actions to take to improve overall sales consistency and performance. Critique the reliance on skewness as a key indicator in ABC Electronics’ sales data analysis. If the sales distribution for home appliances in the West region is highly positively skewed, how should management interpret this result, and what strategic actions would you recommend to address the underlying causes and optimize sales performance? (5 Marks)

Ans 2b.

Introduction

Sales data analysis often goes beyond averages and totals, with managers paying attention to the shape of distribution. In the West region of ABC Electronics, sales of home appliances are reported as highly positively skewed. This means that while a few stores record exceptionally high sales, most outlets perform below the average. Relying only on skewness can be