Question

Match List - I with List - II

List - I (Property)	List - II (Definition)
A. Skewness	IV. Measure of departure from symmetry
B. Kurtosis	II. Measure of the degree of peakedness of a distribution
C. Variance	III. Square of standard deviation
D. Range	I. Difference between highest and least values of the variable

• A. A-IV, B-III, C-II, D-I
• B. A-IV, B-II, C-III, D-I
• C. A-II, B-III, C-IV, D-I
• D. A-II, B-IV, C-III, D-I

Hint:

To remember the difference: Skewness is about "lean" (left or right), while Kurtosis is about "height/peak" (tall or flat).

Answer 1

The Correct Option is B

Concept: Descriptive statistics use various measures to characterize the shape, spread, and central tendency of a dataset. Understanding these properties is essential for interpreting the distribution of data.

Step 1: Matching Shape and Symmetry.

• Skewness (A): This refers to the lack of symmetry in a distribution. A perfectly symmetrical distribution has zero skewness. Therefore, it is a Measure of departure from symmetry (IV).
• Kurtosis (B): This describes the "fatness" of the tails or the Measure of the degree of peakedness (II) of a distribution compared to a normal distribution.

Step 2: Matching Spread and Variation.

• Variance (C): By mathematical definition, variance is the average of the squared deviations from the mean, which is equivalent to the Square of standard deviation (III).
• Range (D): This is the simplest measure of dispersion, defined as the Difference between the highest and least values (I) in a dataset.

Step 3: Conclusion.
Mapping the pairs gives us: A-IV, B-II, C-III, D-I. This matches Option (2).