The Pearson Coefficient of Skewness is a measure that helps to determine the asymmetry of the probability distribution of a real-valued random variable about its mean. If the result of the Pearson Coefficient of Skewness gives a positive value, it indicates that the distribution is described as:

c. Skewed to the right

A positive skewness implies that the tail on the right side of the distribution is longer or fatter than the left side.

Therefore, the correct answer is:

c. Skewed to the right

Do you want any more details or have any questions?

Here are some more questions you might find interesting:

1. What is the formula for the Pearson Coefficient of Skewness?
2. How do you interpret a negative Pearson Coefficient of Skewness?
3. What are other measures of skewness besides the Pearson Coefficient?
4. How does skewness affect the mean and median of a distribution?
5. Can you give an example of a real-life dataset that might exhibit right skewness?

Tip: Understanding the skewness of a dataset is crucial in data analysis as it helps in identifying the direction and extent of asymmetry in the data distribution.