Question

What does the Foot sign/technique indicate when the right foot has a positive skew?

A) Majority falling above the mean
B) Normal distribution
C) Majority falling below the mean
D) No correlation

Answer 1

In a distribution with a positive skew, the majority of data points are located to the left of the mean, leading to a majority falling below the mean.

Step-by-step explanation:

Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. In a positive skew or right skew, the tail on the right side of the distribution is longer or fatter than the left side. It indicates that the majority of the data points fall below the mean. In such a distribution, the mean is typically greater than the median, and the median is often greater than the mode due to the long tail stretching to the right. This is because the outliers or longer tail pull the mean further to the right.

Normal distributions are symmetric and have no skew. When mentioned in the context of specific statistical distributions such as the F distribution or chi-square distribution, the skewness defines the shape of the probability distribution curve and the nature of the statistical test, typically seen in right-tailed tests.