Stikprøvevariationen

Stikprøvevariationen, also known as sampling variation or random sampling error, refers to the natural and expected deviation between a sample statistic and the corresponding population parameter. When a subset of individuals or items (a sample) is selected from a larger group (a population) to make inferences about that population, the characteristics of the sample will rarely be exactly the same as the characteristics of the entire population. This difference is stikprøvevariationen.

For example, if a researcher wants to estimate the average height of all adult males in a country, they might measure the height of a random sample of 100 men. The average height of this sample will likely be close to the true average height of all adult males in the country, but it is highly unlikely to be identical. The difference between the sample average and the population average is due to stikprøvevariationen.

This variation is inherent in the process of sampling. Even if the sampling is done perfectly randomly, different samples drawn from the same population will yield different results. The magnitude of stikprøvevariationen is influenced by factors such as the size of the sample (larger samples generally lead to less variation) and the variability within the population itself (more diverse populations tend to have greater sampling variation). Understanding and accounting for stikprøvevariationen is crucial in statistical inference to ensure that conclusions drawn from sample data are reliable.