UGC NET Questions (Paper – 1)

Kurtosis describes the degree of peakedness and tail heaviness of a distribution compared to the normal curve. High kurtosis (leptokurtic) indicates a sharp peak and heavy tails, while low kurtosis (platykurtic) reflects a flatter peak and lighter tails. Understanding kurtosis helps researchers judge whether data meet assumptions for statistical tests and whether outliers may be problematic. Thus, the statistic described in the stem is correctly called kurtosis.

Option A:
Dispersion is a general concept referring to spread in data, including measures like range and variance, but it does not specifically distinguish between peaked and flat distributions.

Option B:
Skewness deals with asymmetry of the distribution, focusing on whether one tail is longer than the other, which is different from the height and tail heaviness measured by kurtosis.

Option C:
Kurtosis provides insight into how concentrated scores are around the mean and how extreme values contribute to tail thickness, which influences the probability of outliers. These properties correspond exactly to the description of peakedness in the stem, so this option is correct.

Option D:
Reliability concerns consistency of measurement across time or items and is unrelated to the shape of frequency distributions of a single variable.