Answer:
A. Sampling units of different sizes yield different estimates of sample variance because the larger the unit, the more variation is likely to be captured within it.
B. A Type II error is a statistical error that occurs when we fail to reject a null hypothesis that is actually false. This means that we fail to identify a significant relationship or difference between variables when one exists.
C. Increasing variability in population characteristics can increase our sample variance as it makes it more difficult to capture a representative sample of the population. Highly clumped or aggregated animals, for example, may be overrepresented or underrepresented in our sample depending on where our sampling units are placed.
D. We can adapt our sampling to reduce sample variance by using more stratified or systematic sampling methods that ensure a more representative sample of the population. For example, we could use a random sampling design with a larger number of smaller sampling units to capture more variation in the population. Alternatively, we could use a systematic grid or transect to ensure that our sampling units are spaced evenly across the landscape and capture a representative range of population characteristics.
Step-by-step explanation: