English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The simplest, most common paired samples consist of observations from twopopulations, with each observed response from one population corresponding toan observed response from the other population at the same value of an ordinalcovariate. The pair of observed responses (one from each population) at thesame value of the covariate is known as a "matched pair" (with the matchingbased on the value of the covariate). A graph of cumulative differences betweenthe two populations reveals differences in responses as a function of thecovariate. Indeed, the slope of the secant line connecting two points on thegraph becomes the average difference over the wide interval of values of thecovariate between the two points; i.e., slope of the graph is the averagedifference in responses. ("Average" refers to the weighted average if thesamples are weighted.) Moreover, a simple statistic known as the Kuiper metricsummarizes into a single scalar the overall differences over all values of thecovariate. The Kuiper metric is the absolute value of the total difference inresponses between the two populations, totaled over the interval of values ofthe covariate for which the absolute value of the total is greatest. The totalshould be normalized such that it becomes the (weighted) average over allvalues of the covariate when the interval over which the total is taken is theentire range of the covariate (i.e., the sum for the total gets divided by thetotal number of observations, if the samples are unweighted, or divided by thetotal weight, if the samples are weighted). This cumulative approach is fullynonparametric and uniquely defined (with only one right way to construct thegraphs and scalar summary statistics), unlike traditional methods such asreliability diagrams or parametric or semi-parametric regressions, whichtypically obscure significant differences due to their parameter settings.

Cumulative differences between paired samples