DBB1219 STATISTICS FOR MANAGERS JAN FEB 2026

Description

SESSION	APR – AUG 2026
PROGRAM	BACHELOR OF BUSINESS ADMINISTRATION (BBA)
SEMESTER	2
COURSE CODE & NAME	DBB1219 STATISTICS FOR MANAGERS

 

Assignment Set – 1

 

Q.1. Find the A.M from the following data: Weights in (Kgs.): 35, 40, 45, 50, 55, 60 | Number of men: 12, 18, 24, 16, 6, 4 (10 Marks)

Ans 1.

Arithmetic Mean

The Arithmetic Mean (AM) is the most important and widely utilized measure of central tendencies in the field of statistics. The calculation is done by subdividing the sum of the values observed by the total amount of observations. The arithmetic mean provides one value representative that provides a complete summary of the data, making it the most important summary statistic for quantitative data analysis in making business decisions.

In the context of a frequency distribution, where each value occurs multiple times as indicated by its

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Q.2. The weekly salaries of a group of employees are given in the following table. Find the mean and standard deviation of the salaries. Salary (Rs.): 75, 80, 85, 90, 95, 100 | No. of persons: 3, 7, 18, 12, 6, 4 (10 Marks)

Ans 2.

Standard Deviation

The Standard Deviation (SD) is the most significant and widely applied measure of dispersion used in statistical analysis. Although the arithmetic means determines the primary value of a dataset, the standard deviation measures the degree to which individual observations are spread from that central number. Small standard deviations indicate that data elements are situated tightly around the median, however, a high standard deviation signifies that data points are

 

 

Q.3. Calculate Pearson’s coefficient of correlation from the following data. Take 65 and 70 as the assumed averages of the variables x and y respectively. X: 45, 55, 56, 58, 60, 65, 68, 70, 75, 80, 85 | Y: 56, 40, 48, 60, 62, 64, 65, 70, 74, 82, 90 (10 Marks)

Ans 3.

Pearson’s Coefficient of Correlation

Karl Pearson’s Coefficient of Correlation (r) is one of the most popular measures of the linear relation between two quantitative variables. It is a measure of both intensity and direction of the relationship between two variables. It’s expressed as a single numeric value ranging from -1 to +1. A value of +1 indicates a positive, linearly perfect relationship. That is, as one variable rises, the other increases proportionally. If you see a value of -1, that indicates the perfect linear relationship between negative and positive in which the one variable grows, the other decreases

 

 

 

 

 

Assignment Set – 2

 

Q.4. Calculate the regression equations of X on Y and Y on X for the following data: X: 10, 12, 13, 17, 18 | Y: 5, 6, 7, 9, 13. Also determine the value of the coefficient of correlation. (10 Marks)

Ans 4.

Regression Analysis

Regression analysis is a potent method of statistical analysis that establishes an effective mathematical connection among two variables. It allows to predict the value in one particular variable (the dependent variable) based on the known value of a separate variable (the dependent variable). For simple bivariate analysis, we create an uniform straight line that is the best fitting through the data points using the method of least squares. It reduces the horizontal distances

 

 

Q.5. a) Calculate Fisher’s Quantity Index from the following data and show that it satisfies Time Reversal Test. [Data: Commodity P: Base Price=10, Base Value=200, Current Price=12, Current Value=300 | Q: Base Price=8, Base Value=108, Current Price=10, Current Value=220 | R: Base Price=20, Base Value=160, Current Price=25, Current Value=250 | S: Base Price=18, Base Value=144, Current Price=20, Current Value=140 | T: Base Price=35, Base Value=280, Current Price=30, Current Value=300] (10 Marks)

Ans 5.

Fisher’s Index Number

Index numbers are statistical devices to measure changes in the worth of a variable, or group of variables in periods of time or between locations. These numbers are calculated as percentages to the base period of reference. They are called economic barometers as they distill complex variations in prices, quantities of costs or other economic variables into a common number. Business management index numbers are essential for studying the rate of inflation, comparing purchasing power across periods and adjusting financial information for price adjustments, and

 

 

Q.6. From the following data calculate the 4 yearly moving average and determine the trend values. Year: 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024 | Value: 50, 36.5, 43, 44.5, 38.9, 38.1, 32.6, 41.7, 41.1, 33.8 (10 Marks)

Ans 6.

Moving Average – Concept and Time Series Analysis

Time series are the sequence of numeric data points gathered or recorded over successive, equal intervals of time. Time series analysis is the analytical method that is used to study and identify meaningful patterns within the data. Each time-series is believed to consist of four elements: the longer-term Trend (T) is the continuous upward and downward motion over the course of many years; the Cyclical variations (C), representing wavelike fluctuation over multi-year business cycles and the Seasonal variance (S) is a representation of regular, periodic changes within each