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Im Mai 2012 fand in Hamburg erstmals das „Junge Forum Hochschul- und Mediendidaktik“ statt, im Juni 2013 folgte in Potsdam die zweite Auflage als „Junges Forum Medien und Hochschulentwicklung“. 2014 wurde das dritte „Forum“ in Dresden und 2015 das vierte in Düsseldorf ausgerichtet. Das fünfte Forum wird 2016 an der Technischen Universität Darmstadt stattfinden. Initiiert und organisiert wird die Veranstaltung stets von jungen Praktikerinnen und Praktikern sowie Forscherinnen und Forschern mit dem Ziel, dem ‚Nachwuchs‘ in diesem Bereich ein Austauschforum zu geben. Der vorliegende Artikel stellt die konzeptionellen Überlegungen vor, die hinter diesen Treffen stehen. Er zeigt im Rückgriff auf Netzwerktheorie und aktuelle Diskussionen um Professionalisierung und Third Space, wieso für dieses Format ein aktueller Bedarf besteht, und begründet dann im Rückgriff auf didaktische Konzepte auch die methodische Gestaltung der Veranstaltungen. Unsere These: Das kooperative Lernen in Netzwerken ist ein wichtiger Baustein für die Professionalisierung des hochschul- und mediendidaktischen Nachwuchses.
The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.
On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.
The efficiency concepts of Bahadur and Pitman are used to compare the Wilcoxon tests in paired and independent survey samples. A comparison through the length of corresponding confidence intervals is also done. Simple conditions characterizing the dominance of a procedure are derived. Statistical tests for checking these conditions are suggested and discussed.
In a special paired sample case, Hotelling’s T² test based on the differences of the paired random vectors is the likelihood ratio test for testing the hypothesis that the paired random vectors have the same mean; with respect to a special group of affine linear transformations it is the uniformly most powerful invariant test for the general alternative of a difference in mean. We present an elementary straightforward proof of this result. The likelihood ratio test for testing the hypothesis that the covariance structure is of the assumed special form is derived and discussed. Applications to real data are given.
Hotelling’s T² tests in paired and independent survey samples are compared using the traditional asymptotic efficiency concepts of Hodges–Lehmann, Bahadur and Pitman, as well as through criteria based on the volumes of corresponding confidence regions. Conditions characterizing the superiority of a procedure are given in terms of population canonical correlation type coefficients. Statistical tests for checking these conditions are developed. Test statistics based on the eigenvalues of a symmetrized sample cross-covariance matrix are suggested, as well as test statistics based on sample canonical correlation type coefficients.