Skewness refers to asymmetry in a statistical distribution. It can be quantified to define the extent to which a distribution differs from a normal distribution.

Key points:

• A left-skewed distribution (negatively-skewed) has a long left tail, and the mean is to the left of the peak.
• A right-skewed distribution (positively-skewed) has a long right tail, and the mean is to the right of the peak.

Option C correctly states that skewness refers to asymmetry and that in positively-skewed distributions, the mean is to the right of the peak.

Why other options are incorrect:

• Option A: Incorrect because skewness refers to asymmetry, not symmetry.
• Option B: Incorrect because in negatively-skewed distributions, the mean is to the left of the peak, not to the right.
• Option D: Incorrect because in left-skewed distributions, the mean does not coincide with the peak; it is to the left of the peak.