4 ms·

Plus, some personal variability. 3-4mo is a good amount to take into account, if you ever need to.

by brnt 3y ago

moi2388 3y ago
Variance generally goes both ways. If the true average is 2-2,5 months you should take that as average expected value, not 4 months. Following your logic it’s equally valid to claim 0 months lol
- brnt 3y ago
  No, thats not how calculating quantities with tolerances work. Lol.
- anon291 3y ago
  Without any further information, given what we know about sperm production (it's a physical process for which we're measuring time), the expected distribution is not normal (probably exponential or something). The claim that 'variance goes both ways' is wrong. Variance can only go one way. It can go one way mostly, or it can go bothways, or it can take a U shape. It all depends on the distribution of the events. If we take it to be a simple exponential distribution with mean 66 days, then lambda = 1/66. and variance is 4356 or a standard deviation of 66 days as well. In that case, by month 4, about 83% of men would be expected to have sperm in their semen. To delve deeper, what you're missing here is the idea of skewness and kurtosis. These are the 'higher moments' of the probability distribution function (natural extensions of mean, variance, etc). In particular, the skewness is where you're getting hung up. You assume in your first sentence that the skewness of every pdf is zero (i.e., it 'goes both ways'). That is not generally the case. In particular, the skewness of the 'time to first sperm' distribution must be very positive because it can never be below zero.
  - moi2388 3y ago
    Most biological processes are modelled and assumed as being normally distributed due to the central limit theorem. If you were talking about how much sperm they had exponential would indeed be better. But we’re not. Just if they have any. If the average time it takes is 2,5 months, you should expect to wait on average 2,5 months, not 4. That is indeed not the same as asking when do 83% of men have sperm, since 83% is not the average.
    - anon291 3y ago
      > Most biological processes are modelled and assumed as being normally distributed due to the central limit theorem. Things cannot be distributed where the distribution has values the thing can never have. The time until an event cannot be negative. The cdf of a normal distribution always has a non-zero value at zero. There is no chance a sperm is ejaculated before it's made. That's a logical impossibility. Thus time to first sperm is absolutely not normally distributed.

Plus, some personal variability. 3-4mo is a good amount to take into account, if you ever need to.

by brnt 3y ago

Plus, some personal variability. 3-4mo is a good amount to take into account, if you ever need to.

Variance generally goes both ways. If the true average is 2-2,5 months you should take that as average expected value, not 4 months. Following your logic it’s equally valid to claim 0 months lol

brnt 3y ago
No, thats not how calculating quantities with tolerances work. Lol.
anon291 3y ago
Without any further information, given what we know about sperm production (it's a physical process for which we're measuring time), the expected distribution is not normal (probably exponential or something). The claim that 'variance goes both ways' is wrong. Variance can only go one way. It can go one way mostly, or it can go bothways, or it can take a U shape. It all depends on the distribution of the events. If we take it to be a simple exponential distribution with mean 66 days, then lambda = 1/66. and variance is 4356 or a standard deviation of 66 days as well. In that case, by month 4, about 83% of men would be expected to have sperm in their semen. To delve deeper, what you're missing here is the idea of skewness and kurtosis. These are the 'higher moments' of the probability distribution function (natural extensions of mean, variance, etc). In particular, the skewness is where you're getting hung up. You assume in your first sentence that the skewness of every pdf is zero (i.e., it 'goes both ways'). That is not generally the case. In particular, the skewness of the 'time to first sperm' distribution must be very positive because it can never be below zero.
- moi2388 3y ago
  Most biological processes are modelled and assumed as being normally distributed due to the central limit theorem. If you were talking about how much sperm they had exponential would indeed be better. But we’re not. Just if they have any. If the average time it takes is 2,5 months, you should expect to wait on average 2,5 months, not 4. That is indeed not the same as asking when do 83% of men have sperm, since 83% is not the average.
  - anon291 3y ago
    > Most biological processes are modelled and assumed as being normally distributed due to the central limit theorem. Things cannot be distributed where the distribution has values the thing can never have. The time until an event cannot be negative. The cdf of a normal distribution always has a non-zero value at zero. There is no chance a sperm is ejaculated before it's made. That's a logical impossibility. Thus time to first sperm is absolutely not normally distributed.