I'm not even sure if they are serious, but I've heard many times that some people refuse to not only trust their computer to generate a random string (which is understandable) but also don't trust themselves to do it. So, instead of simply typing/writing down:
fcC540dfdK45xslLDdfd7dDL92

And then randomly changing a few of those to other ones a few seconds later, such as one in the beginning, one in the middle and one in the end, they use dice which they roll again and again to generate random numbers, which are then treated as "truly random" and thus "truly secure".
Why would a dice roll be "more random" than simply coming up with a sequence in your head, and then changing some of them?
I simply don't believe that this could possibly be "not secure". Why the need to do the very tedious dice rolling? It feels like a ritual that they go through, based not on logic and reason, but on some sort of delusion that their brain is going to generate the same sequence as others who guess it, or a computer, even though they also change some of them after the phrase is "done".
I don't understand this. Is there anything that speaks for this practice as being "more random"/"more secure"?

In short, it is more than a belief: there is strong evidence that humans are not good entropy sources. There is a test for this

Man vs. Machine. Or, why Man is not a Particularly Good Source of Entropy.

Try to win!
So we don't rely on whether generating a random number from the mind or random keyboard typings and mouse movements that seem like a monkey playing on the computer from outsiders. We rely on good entropy sources like the /dev/urandom. That kind of sources comes from good research.
Some researches on supporting this;

1972, W. A. Wagenaar, Generation of random sequences by human subjects: a critical survey of the literature

1997, Brugger, P., Variables that influence the generation of random sequences: An update. Perceptual and Motor Skills

2005, Persaud, N, Humans can consciously generate random number sequences: A possible test for artificial intelligence. Medical hypotheses, 65(2), 211-21

2012, Schulz et. al, Analysing Humanly Generated Random Number Sequences: A Pattern-Based Approach

2012, Williams and  Griffiths Why Are People Bad at Detecting Randomness? A Statistical Argument

2014, Towse et. al, Not all numbers are equal: preferences and biases among children and adults when generating random sequences



Other online tests;

not so random with the collected results.

