ZweiseitenSchätzungen

ZweiseitenSchätzungen is a statistical concept that refers to estimates and inferential procedures that account for uncertainty on both sides of a parameter’s distribution. In contrast to one-sided estimates, which focus on deviation in a single direction, zweiseitenSchätzungen express uncertainty with an interval or range that covers possible values on both sides of the point estimate.

In practice, the term is closely associated with two-sided methods such as confidence intervals and two-sided hypothesis tests. A common example is the construction of a two-sided confidence interval for a parameter θ̂ with standard error SE: θ̂ ± z_(0.975)·SE for large samples (or θ̂ ± t_(n-1, 0.975)·SE for small samples). For hypothesis testing, a two-sided test against H0: θ = θ0 yields a p-value of 2·P(|Z| ≥ |Z_obs|) in the normal approximation. These procedures assume, at least approximately, symmetry in the sampling distribution around the estimate.

Applications span estimating means, proportions, and differences between groups, as well as effect sizes in fields such as medicine, psychology, and economics. The primary advantage of zweiseitenSchätzungen is intuitive interpretation: they quantify uncertainty in both directions and provide balanced evidence about where the true parameter lies. Limitations arise when the underlying distribution is highly skewed, bounded, or when sample sizes are small, in which case two-sided methods may be conservative or inappropriate and one-sided alternatives might be more suitable.

Terminology varies in practice. In many German texts, terms like zwei-seitige Konfidenzintervalle or zweiseitige Hypothesentests are used, with zweiseitenSchätzungen serving as a broader or informal label for the associated two-sided inferences.