Sampling
Usually we cannot observe an entire biological population, so a sample is used to learn about it.
Sample statistics
For observations \(X_1,\ldots,X_n\), the sample mean is
\[\bar X=\frac1n\sum_{i=1}^nX_i.\]If observations are independent with population mean \(\mu\) and variance \(\sigma^2\), then
\[E[\bar X]=\mu,\qquad \operatorname{Var}(\bar X)=\frac{\sigma^2}{n}.\]Representativeness
A large sample does not automatically remove bias. Sampling design matters if some individuals, locations or times are systematically more likely to be observed.
Key idea. Statistical inference depends both on sample size and on how the sample was obtained.