Measures of Dispersion - Online Test

Q1. What would happen to the variance of a data set if we multiplied every observation by 5?
Answer : Option B
Explaination / Solution:

Change in variance is the square of change in scale.

Q2. While drawing Lorenz curve zero of X-axis and 100 on Y-axis are joined by a line. This line is known as
Answer : Option A
Explaination / Solution:
No Explaination.


Q3. The _______________ is the easiest measure of dispersion to calculate.
Answer : Option A
Explaination / Solution:

It is easy to calculate because of a simple formula R= L-S where L is largest observation and S is smallest observation.

Q4. Which information is false regarding Lorenz curve
Answer : Option D
Explaination / Solution:

The Lorenz curve, developed by Max O Lorenz in 1905, is a graphical representation of the distribution of the income or of wealth. It is used to represent inquality of the wealth distribution.

Q5. In case of open-ended classes, an appropriate measure of dispersion to be used is
Answer : Option A
Explaination / Solution:

As it is not much affected by extreme situations.

Q6. When should measures of location and dispersion be computed from grouped data rather than from individual data values?
Answer : Option C
Explaination / Solution:
No Explaination.


Q7. The descriptive measure of dispersion that is based on the concept of a deviation about the mean is
Answer : Option A
Explaination / Solution:

Standard deviation for a given set of observations is defined as root mean square deviation when deviations are taken from mean.

Q8. The numerical value of the standard deviation can never be
Answer : Option C
Explaination / Solution:

As it is calculated from sum of squared deviations which can never be negative.

Q9. The variance can never be
Answer : Option B
Explaination / Solution:

It is a square of standard deviation and square of anything is non negative.

Q10. Which of the following symbols represents the standard deviation of the population?
Answer : Option A
Explaination / Solution:
No Explaination.