Normal distribution {dprop}

Compute the distributional properties of the normal distribution

Description

Compute the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the normal distribution.

Usage

d_normal(alpha, beta)

Arguments

alpha

Location parameter of the normal distribution (\alpha\in\left(-\infty,+\infty\right)).

beta

The strictly positive scale parameter of the normal distribution (\beta > 0).

Details

The following is the probability density function of the normal distribution:

f(x)=\frac{1}{\beta\sqrt{2\pi}}e^{-0.5\left(\frac{x-\alpha}{\beta}\right)^{2}},

where x\in\left(-\infty,+\infty\right), \alpha\in\left(-\infty,+\infty\right) and \beta > 0. The parameters \alpha and \beta represent the mean and standard deviation, respectively.

Value

d_normal gives the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the normal distribution.

Author(s)

Muhammad Imran.

R implementation and documentation: Muhammad Imran [e-mail].

References

Patel, J. K., & Read, C. B. (1996). Handbook of the normal distribution (Vol. 150). CRC Press.

See Also

d_lnormal

Examples

d_normal(4,0.2)