Utah's state board members said last week that they support its state's test participation law which conflicts with the Every Student Succeeds Act.

The state's closely watched bid falls shy of full approval from federal reviewers.

The Every Student Succeeds Act allows up to seven states to try out new kinds of tests in a handful of districts before taking them statewide.

Teachers in North Carolina and Oregon plan to walk out of their classrooms in protest in May.

Institute of Ophthalmology., producer.

London-Sydney Marathon -- History.

McMillan, Peter -- Travel.

Down syndrome -- Diagnosis -- Moral and ethical aspects.

Pokémon Go (Game) -- Social aspects.

A sea of red swept the capitals of North and South Carolina on Wednesday, as thousands of teachers turned out to demand higher pay and more school funding.

Cambridge : printed by C.J. Clay at the University Press, 1887.

London : D. Bogue, 1881.

Gottingen : Dieterich, 1843.

Berlin : Karger, 1910.

Berlin : Karger, 1905.

[Edinburgh] : [publisher not identified], 1870.

London : H. Renshaw, 1849.

Paris : J.-B. Baillière, 1905.

As Oklahoma teachers prepare for day four of their statewide walkout, here's a guide to the larger picture of teacher protests.

[Rome?]

Si stampano in Roma (alla Pace ; all'insegna di Parigi) : per Giovan Jacomo Rossi, [1641?]

As civic education undergoes a renaissance in schools, educators are looking beyond standardized tests to determine whether the lessons empower students to embrace civic behaviors, like voting or volunteering.

A federal investigation of Chicago's failures to respond to sexual violence in schools raises troubling questions for school districts nationwide.

British Columbia Premier John Horgan has offered the NHL a place to play if the league can find a way to resume the season. Speaking at a COVID-19 media briefing Wednesday, Horgan said he has written a letter to both NHL Commissioner Gary Bettman and NHL Players’ Association head Donald Fehr to let them know B.C. is “a place to potentially restart the NHL assuming the games would be played without audiences, but instead played for television.” The NHL suspended its season March 12 with 189 regular-season games left.

In a video posted along with the schedule, the Seahawks gave season tickets to 12 workers who had been nominated for consideration. The 12 were told of receiving season tickets in video calls with Seahawks players Shaquill and Shaquem Griffin, DK Metcalf, Tyler Lockett, Will Dissly and coach Pete Carroll. The Royal St. John’s Regatta in Canada has been canceled because of the COVID-19 pandemic.

A 24-team Stanley Cup Playoffs? Here's a look at the latest NHL buzz and a hypothetical Flyers matchup. By Jordan Hall

The century-old Reno Rodeo has canceled the 10-day event in June because of the coronavirus pandemic. Reno Rodeo President Craig Downie said in a letter to the rodeo’s board of directors that canceling the event scheduled for June 18-27 was necessary to ensure the safety of participants, fans, vendors, sponsors and volunteers. General Manager George Combs said it was a difficult decision, made in consultation with health experts as well as the Professional Rodeo Cowboys Association.

Troy Brouwer scored the game-winning goal as the Capitals beat the Blackhawks at Nationals Park on Jan. 1, 2015. Relive the excitement with Monday night's replay.

Rockville, Maryland : National Institute on Drug Abuse, 1986.

Rockville, Maryland : National Institute on Drug Abuse, 1978.

Jean-Marc Bardet, Kare Kamila, William Kengne.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 2009--2052.

Abstract:
This paper studies the model selection problem in a large class of causal time series models, which includes both the ARMA or AR($infty $) processes, as well as the GARCH or ARCH($infty $), APARCH, ARMA-GARCH and many others processes. To tackle this issue, we consider a penalized contrast based on the quasi-likelihood of the model. We provide sufficient conditions for the penalty term to ensure the consistency of the proposed procedure as well as the consistency and the asymptotic normality of the quasi-maximum likelihood estimator of the chosen model. We also propose a tool for diagnosing the goodness-of-fit of the chosen model based on a Portmanteau test. Monte-Carlo experiments and numerical applications on illustrative examples are performed to highlight the obtained asymptotic results. Moreover, using a data-driven choice of the penalty, they show the practical efficiency of this new model selection procedure and Portemanteau test.

Christophe A. N. Biscio, Nicolas Chenavier, Christian Hirsch, Anne Marie Svane.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1024--1074.

Abstract:
We introduce tests for the goodness of fit of point patterns via methods from topological data analysis. More precisely, the persistent Betti numbers give rise to a bivariate functional summary statistic for observed point patterns that is asymptotically Gaussian in large observation windows. We analyze the power of tests derived from this statistic on simulated point patterns and compare its performance with global envelope tests. Finally, we apply the tests to a point pattern from an application context in neuroscience. As the main methodological contribution, we derive sufficient conditions for a functional central limit theorem on bounded persistent Betti numbers of point processes with exponential decay of correlations.

We study the identity testing problem in the context of spin systems or undirected graphical models, where it takes the following form: given the parameter specification of the model $M$ and a sampling oracle for the distribution $mu_{M^*}$ of an unknown model $M^*$, can we efficiently determine if the two models $M$ and $M^*$ are the same? We consider identity testing for both soft-constraint and hard-constraint systems. In particular, we prove hardness results in two prototypical cases, the Ising model and proper colorings, and explore whether identity testing is any easier than structure learning. For the ferromagnetic (attractive) Ising model, Daskalakis et al. (2018) presented a polynomial-time algorithm for identity testing. We prove hardness results in the antiferromagnetic (repulsive) setting in the same regime of parameters where structure learning is known to require a super-polynomial number of samples. Specifically, for $n$-vertex graphs of maximum degree $d$, we prove that if $|eta| d = omega(log{n})$ (where $eta$ is the inverse temperature parameter), then there is no polynomial running time identity testing algorithm unless $RP=NP$. In the hard-constraint setting, we present hardness results for identity testing for proper colorings. Our results are based on the presumed hardness of #BIS, the problem of (approximately) counting independent sets in bipartite graphs.

Victor Coscrato, Rafael Izbicki, Rafael B. Stern.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 230--250.

Abstract:
Despite its common practice, statistical hypothesis testing presents challenges in interpretation. For instance, in the standard frequentist framework there is no control of the type II error. As a result, the non-rejection of the null hypothesis $(H_{0})$ cannot reasonably be interpreted as its acceptance. We propose that this dilemma can be overcome by using agnostic hypothesis tests, since they can control the type I and II errors simultaneously. In order to make this idea operational, we show how to obtain agnostic hypothesis in typical models. For instance, we show how to build (unbiased) uniformly most powerful agnostic tests and how to obtain agnostic tests from standard p-values. Also, we present conditions such that the above tests can be made logically coherent. Finally, we present examples of consistent agnostic hypothesis tests.

Fábio P. Lima, Francisco Cribari-Neto.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 18--34.

Abstract:
We address the issue of performing testing inference in small samples in the class of beta regression models. We consider the likelihood ratio test and its standard bootstrap version. We also consider two alternative resampling-based tests. One of them uses the bootstrap test statistic replicates to numerically estimate a Bartlett correction factor that can be applied to the likelihood ratio test statistic. By doing so, we avoid estimation of quantities located in the tail of the likelihood ratio test statistic null distribution. The second alternative resampling-based test uses a fast double bootstrap scheme in which a single second level bootstrapping resample is performed for each first level bootstrap replication. It delivers accurate testing inferences at a computational cost that is considerably smaller than that of a standard double bootstrapping scheme. The Monte Carlo results we provide show that the standard likelihood ratio test tends to be quite liberal in small samples. They also show that the bootstrap tests deliver accurate testing inferences even when the sample size is quite small. An empirical application is also presented and discussed.

Dan J. Spitzner.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 861--893.

Abstract:
This article proposes a calibration scheme for Bayesian testing that coordinates analytically-derived statistical performance considerations with expert opinion. In other words, the scheme is effective and meaningful for incorporating objective elements into subjective Bayesian inference. It explores a novel role for default priors as anchors for calibration rather than substitutes for prior knowledge. Ideas are developed for use with multiplicity adjustments in multiple-model contexts, and to address the issue of prior sensitivity of Bayes factors. Along the way, the performance properties of an existing multiplicity adjustment related to the Poisson distribution are clarified theoretically. Connections of the overall calibration scheme to the Schwarz criterion are also explored. The proposed framework is examined and illustrated on a number of existing data sets related to problems in clinical trials, forensic pattern matching, and log-linear models methodology.

Hedibert F. Lopes, Nicholas G. Polson.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 745--755.

Abstract:
Bayesian hypothesis testing is re-examined from the perspective of an a priori assessment of the test statistic distribution under the alternative. By assessing the distribution of an observable test statistic, rather than prior parameter values, we revisit the seminal paper of Edwards, Lindman and Savage ( Psychol. Rev. 70 (1963) 193–242). There are a number of important take-aways from comparing the Bayesian paradigm via Bayes factors to frequentist ones. We provide examples where evidence for a Bayesian strikingly supports the null, but leads to rejection under a classical test. Finally, we conclude with directions for future research.

Jamye Curry, Xin Dang, Hailin Sang.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 3, 425--454.

Abstract:
We study a rank based univariate two-sample distribution-free test. The test statistic is the difference between the average of between-group rank distances and the average of within-group rank distances. This test statistic is closely related to the two-sample Cramér–von Mises criterion. They are different empirical versions of a same quantity for testing the equality of two population distributions. Although they may be different for finite samples, they share the same expected value, variance and asymptotic properties. The advantage of the new rank based test over the classical one is its ease to generalize to the multivariate case. Rather than using the empirical process approach, we provide a different easier proof, bringing in a different perspective and insight. In particular, we apply the Hájek projection and orthogonal decomposition technique in deriving the asymptotics of the proposed rank based statistic. A numerical study compares power performance of the rank formulation test with other commonly-used nonparametric tests and recommendations on those tests are provided. Lastly, we propose a multivariate extension of the test based on the spatial rank.

Khamis K. Said, Wei Ning, Yubin Tian.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 280--300.

Abstract:
In this paper, we study the change point problem for the skew normal distribution model from the view of model selection problem. The detection procedure based on the modified information criterion (MIC) for change problem is proposed. Such a procedure has advantage in detecting the changes in early and late stage of a data comparing to the one based on the traditional Schwarz information criterion which is well known as Bayesian information criterion (BIC) by considering the complexity of the models. Due to the difficulty in deriving the analytic asymptotic distribution of the test statistic based on the MIC procedure, the bootstrap simulation is provided to obtain the critical values at the different significance levels. Simulations are conducted to illustrate the comparisons of performance between MIC, BIC and likelihood ratio test (LRT). Such an approach is applied on two stock market data sets to indicate the detection procedure.

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker.

Source: Statistics Surveys, Volume 12, 136--172.

Abstract:
Data on how many scientific findings are reproducible are generally bleak and a wealth of papers have warned against misuses of the $p$-value and resulting false findings in recent years. This paper discusses the question of what we can(not) learn from the $p$-value, which is still widely considered as the gold standard of statistical validity. We aim to provide a non-technical and easily accessible resource for statistical practitioners who wish to spot and avoid misinterpretations and misuses of statistical significance tests. For this purpose, we first classify and describe the most widely discussed (“classical”) pitfalls of significance testing, and review published work on these misuses with a focus on regression-based “confirmatory” study. This includes a description of the single-study bias and a simulation-based illustration of how proper meta-analysis compares to misleading significance counts (“vote counting”). Going beyond the classical pitfalls, we also use simulation to provide intuition that relying on the statistical estimate “$p$-value” as a measure of evidence without considering its sample-to-sample variability falls short of the mark even within an otherwise appropriate interpretation. We conclude with a discussion of the exigencies of informed approaches to statistical inference and corresponding institutional reforms.