I'm using R
along with library moments
to generate a small dataset and compute the four initial moments of my data:
- Mean
- Variation
- Skewness
- Kurstosis
The code is shown below. I set a random seed for my PRNG and generates 1000 data points using a normal distribution.
Then, I print four moments two ways. First, I print then individually. Then, I print them using the method all.moments.
library(moments)
set.seed(123)
x = rnorm(1000, sd = 0.02)
print(mean(x));
print(var(x));
print(skewness(x))
print(kurtosis(x))
print(moments::all.moments(x, order.max = 4))
The outputs are shown below.
print(mean(x));
0.0003225573
print(var(x));
0.0003933836
print(skewness(x));
0.06529391
print(kurtosis(x));
2.925747
print(moments::all.moments(x, order.max = 4));
1.000000e+00 3.225573e-04 3.930942e-04 8.889998e-07 4.527577e-07
One may note that both the skewness and the kurtosis of both methods are different.
My question is: Why they give different results? Which result is the right one?