Inferential, Nonparametric Statistics to Assess the Quality of Probabilistic Forecast Systems

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires “climate knowledge”, i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, ra...

A ( brief ) Introduction to Inferential Statistics

The eld of statistics can be divided into two branches, descriptive statistics and inferential statistics. Descriptive statistics, as its name suggests, is concerned with describing a population, or a sample from that population, in terms of numerical measures that are computed from data. Such a numerical measure is called a statistic. If the data used in the computation comes from the whole po...

An Application Of Inferential Statistics To The Factorial Invariance Problem.

Attention has been drawn to the lack of standards for evaluating the degree of goodness of fit of patterns resulting from a principal components analysis of two data sets. An empirical sampling distribution of the statistic average trace (E'E), as E is obtained in the orthogonal Procrustes problem for various orders of A matrices was developed through a Monte Carlo approach. A method is present...

Effect Size vs Inferential Statistics

Chapter 14 . Inferential Statistics , Descriptive Statistics and The Analysis Plan

Provided that the data show that a compound is safe, it is the primary efficacy analysis that determines whether the compound is approved. The secondary analyses support, clarify and confirm, but only one prospectively planned efficacy analysis can be primary in support of an effectiveness claim for a given trial. Why should this be so? And how can we design the trial and set up the primary eff...