UGC NET Questions (Paper – 1)

Skewness indicates whether a distribution is symmetric around the mean or whether one tail is stretched out more than the other. Positive skewness means the tail is longer on the right side with more high-end outliers, while negative skewness means the tail is longer on the left. Assessing skewness helps determine whether parametric tests that assume normality are appropriate or whether transformations might be needed. Therefore, the statistic described in the stem is correctly called skewness.

Option A:
Kurtosis refers to the peakedness or flatness of a distribution relative to normal, not the degree of asymmetry between tails. Although related to distribution shape, it addresses a different aspect than the one in the stem.

Option B:
Skewness summarises how scores pile up toward one side of the mean and taper off on the other, affecting measures like mean and standard deviation. When skewness is large, median and non-parametric methods may give more robust results. These features match the description of asymmetry in the stem, so this option is correct.

Option C:
Variability is a general term for spread in data and is quantified by measures like variance and standard deviation; it does not specifically capture tail asymmetry.

Option D:
Central tendency statistics such as mean or median describe typical values, not the balance of tails, so central tendency is not the correct term here.

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.