How do you test for normality from skewness and kurtosis?

How do you test for normality from skewness and kurtosis?

The normal distribution has a skewness of zero and kurtosis of three. The test is based on the difference between the data’s skewness and zero and the data’s kurtosis and three. The test rejects the hypothesis of normality when the p-value is less than or equal to 0.05.

How do you test if a variable is normally distributed in Stata?

Conducting a normality test in STATA

1. Go to the ‘Statistics’ on the main window.
2. Choose ‘Distributional plots and tests’
3. Select ‘Skewness and kurtosis normality tests’.

How much skewness and kurtosis is normal?

Both skew and kurtosis can be analyzed through descriptive statistics. Acceptable values of skewness fall between − 3 and + 3, and kurtosis is appropriate from a range of − 10 to + 10 when utilizing SEM (Brown, 2006).

Does kurtosis measure normality?

Most often, kurtosis is measured against the normal distribution. If the kurtosis is close to 0, then a normal distribution is often assumed. These are called mesokurtic distributions. If the kurtosis is less than zero, then the distribution is light tails and is called a platykurtic distribution.

How do I know if my data is normally distributed Shapiro-Wilk?

value of the Shapiro-Wilk Test is greater than 0.05, the data is normal. If it is below 0.05, the data significantly deviate from a normal distribution.

How do you test for normality in skewness?

As a general rule of thumb:

1. If skewness is less than -1 or greater than 1, the distribution is highly skewed.
2. If skewness is between -1 and -0.5 or between 0.5 and 1, the distribution is moderately skewed.
3. If skewness is between -0.5 and 0.5, the distribution is approximately symmetric.

What skewness is considered normal?

zero
The skewness for a normal distribution is zero, and any symmetric data should have a skewness near zero.