I didn't make a big point of it, but in our discussion of genetic
drift so far we've assumed everything about populations that we
assumed to derive the Hardy-Weinberg principle, *and* we've
assumed that:

- We can model drift in a finite population as a result of
sampling among haploid gametes rather than as a result of sampling
among diploid genotypes. Since we're dealing with a finite population,
this effectively means that the two gametes incorporated into an
individual could have come from the same parent, i.e.,
self-fertilization occurs when there's random union of gametes in a
finite, diploid population.
- Since we're sampling gametes rather than individuals, we're also
implictly assuming that there aren't separate sexes.
^{14} - The number of gametes any individual has represented in the next
generation is a binomial random variable.
^{15} - The population size is constant.

How do we deal with the fact that one or more of these conditions will
be violated in just about any case we're interested in?^{16} One way would be to develop all the probability
models that incorporate that complexity and try to solve them. That's
nearly impossible, except through computer simulations. Another, and
by far the most common approach, is to come up with a conversion
formula that makes our actual population seem like the ``ideal''
population that we've been studying. That's exactly what * effective population size* is.

The effective size of a population is the size of an ideal population that has the same properties with respect to genetic drift as our actual population does.What does that phrase ``same properties with respect to genetic drift'' mean? Well there are two ways it can be defined.

- Variance effective size
- Inbreeding effective size
- Comments on effective population sizes
- Examples

- Variation in offspring number