There is a standardized transformation which can transform a normal distribution to standard normal distribution:

$$x^{(i)}=frac{x^{(i)}-mu_x}{sigma_x}$$

I am wondering **given a uniform distribution or any other distribution, can we transform it into a standard normal distribution using the above equation?**

It is difficult to see from the following codes.

```
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randint(0, 10000, (1, 100))
y = np.random.randint(0, 4000, (1, 100))
z = np.random.randn(1, 100)
x_s = (x - x.mean()) / x.std()
y_s = (y - y.mean()) / y.std()
# plt.hist(x_s, bins=1)
# plt.show()
import seaborn as sns
# sns.distplot(x, rug=True, bins=None)
sns.distplot(x_s, rug=True, bins=None)
# sns.distplot(z, rug=True, bins=None)
plt.show()
```