Inferenzrechnungen

Inferenzrechnungen, also known as inferential statistics, is a branch of statistics that deals with drawing conclusions or making predictions about a population based on data from a sample of that population. Unlike descriptive statistics, which summarizes and organizes data from a sample, inferential statistics uses probability theory to generalize findings beyond the observed data. The core idea is that a well-chosen sample can provide sufficient information to make informed statements about the larger group from which it was drawn.

Key techniques in inferenzrechnungen include hypothesis testing and estimation. Hypothesis testing involves formulating a null hypothesis (a statement of no effect or no difference) and an alternative hypothesis, and then using sample data to determine whether there is enough evidence to reject the null hypothesis. Estimation, on the other hand, involves using sample statistics to estimate population parameters, such as the mean or proportion. This can be done through point estimation, which provides a single value, or interval estimation, which provides a range of plausible values (confidence interval). The validity of inferences drawn from inferential statistics relies heavily on the assumption that the sample is representative of the population.