04
Sep
Skewness Of Normal Distribution. If a density curve looks the same to the left and to the right such as the bell curve for the normal distribution then it is a symmetric distribution and the skewness coefficient is zero. Notice how these central tendency measures tend to spread when the normal distribution is distorted. It is nearly perfectly symmetrical. Distribution be normal or nearly normal.
Notice how these central tendency measures tend to spread when the normal distribution is distorted. The skewness for a normal distribution is zero and any symmetric data should have a skewness near zero. For any given distribution its skewness can be quantified to represent its variation from a normal distribution. If skewness is less than -1 or greater than 1 the distribution is highly skewed. The lack of symmetry in a distribution is always determined with reference to a normal distribution which is always symmetrical. It is nearly perfectly symmetrical.
As I mentioned earlier the ideal normal distribution is the probability distribution with almost no skewness.
For any given distribution its skewness can be quantified to represent its variation from a normal distribution. It is desirable that for the normal distribution of data the values of skewness should be near to 0. Due to this the value of skewness for a normal distribution is zero. The Skewness measures the symmetry of a distribution. As I mentioned earlier the ideal normal distribution is the probability distribution with almost no skewness. The skewness for a normal distribution is zero and any symmetric data should have a skewness near zero.