meddling with entropy and using a physical source (anything except what your computer generates) should be considered an advanced topic which regular users should not try to perform without first educating themselves on how it is done correctly and are aware of possible biases and other issues that might be involved.

Applying this test to the output of various pseudorandom sequence generators is interesting. The low-order 8 bits returned by the standard Unix rand() function, for example, yields:
Chi square distribution for 500000 samples is 0.01, and randomly would exceed this value more than 99.99 percent of the times.
While an improved generator [Park & Miller] reports:
Chi square distribution for 500000 samples is 212.53, and randomly would exceed this value 97.53 percent of the times.
Thus, the standard Unix generator (or at least the low-order bytes it returns) is unacceptably non-random, while the improved generator is much better but still sufficiently non-random to cause concern for demanding applications.

Entropy values must be sourced from a strong source of randomness. This means flipping a fair coin, rolling a fair dice, noise measurements etc.

An important part of creating a Bitcoin wallet is ensuring the random numbers used to create the wallet are truly random. Physical randomness is better than computer generated pseudo-randomness. The easiest way to generate physical randomness is with dice.