An unusual program in Cincinnati provides academic coaches to help high school players meet eligibility requirements to stay in the game.

About a dozen teachers running for state legislative seats gathered with their supporters in Tulsa for a watch party on election night. The results were better for some than others.

As the national conversation on reopening schools accelerates, experts say the best way to protect vulnerable teachers might be to not have them in school buildings at all.

Frank DeAngelis, who was the principal of Columbine High School from 1996-2014, talks about the steps he took to heal students and staff in the wake of the school shooting.

Former Colorado Gov. John Hickenlooper, who helped initiate a shakeup of Denver Public Schools, has announced that he's running for president as a Democrat in 2020.

As the national conversation on reopening schools accelerates, experts say the best way to protect vulnerable teachers might be to not have them in school buildings at all.

Wisconsin is one of a handful of states where how much schools will get this fall is still being debated in the state capitol.

The leader of a Montana school district spends up to two hours each day grading assignments from students in an online English credit recovery program.

The U.S. Supreme Court will hear arguments remotely in May, including on whether religious schools are exempt from employment discrimination claims brought by lay teachers.

In a case from Montana, conservative justices suggested they were inclined to rule for parents who seek to reinstate a state tax credit funding scholarships for use at religious schools.

State education officials are responding to a state law passed last year requiring them to solicit feedback from the community on the impact of implementing later school start times for middle and high school students.

The Christie administration is arguing that the only way to improve education in the state's poorest districts is to ditch teacher job protections.

In Florida, Indiana, Kansas, North Carolina, Tennessee and Utah, Republicans are arguing that candidates for local and state school boards should run on party tickets.

Federal watchdogs find that Utah inflated its high school graduation rate in the last of a series of reports warning states not to make end runs around the rules for calculating graduation rates.

Too early to just hand him the Heisman Trophy now?

Colts quarterback Philip Rivers is signed for the 2020 season and he hasn't made any decisions about whether he'll keep playing in 2021, but it looks like he knows what he'll be doing when he does hang up his helmet. Rivers said when he signed with the Colts that he looked forward to coaching his [more]

Charter schools in Washington state can continue to receive public funding, the state's high court ruled last week.

"It is timely that the higher education sector examines paths forward to address and indeed engage in the new environment in which it will work in the future. This fellowship explored two approaches to engage students more deeply in their education. The first approach is generally termed 'interdisciplinary studies' where students define their own program of study; the second approach focuses on topic structure where students are given a wide range of choice and in effect can build a topic that suits their interests."--Page iv.

Quin, Tegan, 1980- -- Childhood and youth.

The Kansas Supreme Court has again ruled that the money the state legislature provides its schools is constitutionally inadequate.

The Florida supreme court has ordered a statewide grand jury with a broad mandate to investigate school safety.

Alexandria Area High School was created to accommodate changes in education and technology.

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

A union lobbyist who worked just one day as a substitute teacher is entitled to a pension worth potentially tens of thousands of dollars annually, the Illinois supreme court has ruled.

The Flyers have had quite a bit of luck when drafting players from the Brandon Wheat Kings. Could they keep their streak alive with Braden Schneider in the first round of the 2020 NHL draft? By Brooke Destra

The justices declined to hear the appeal of the Ferguson-Florissant district over its at-large board elections, which lower courts invalidated as violating the Voting Rights Act.

All-Pac-12 talent Mikayla Pivec's career in Corvallis has been memorable to say the least. While it's difficult to choose just three, her top moments include a career-high 19 rebounds against Washington, a buzzer-beating layup against ASU, and breaking Ruth Hamblin's Oregon State rebounding record this year against Stanford.

Arizona's Aari McDonald and Pac-12 Networks' Ashley Adamson discuss the guard's decision to return for her senior season in Tucson and how she now has the opportunity to be the face of the league. McDonald, the Pac-12 Defensive Player of the Year, was one of the nation's top scorers in 2019-20, averaging 20.6 points per game.

Emanuel Ben-David, Bala Rajaratnam.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 580--604.

Abstract:
The Wishart distribution defined on the open cone of positive-definite matrices plays a central role in multivariate analysis and multivariate distribution theory. Its domain of parameters is often referred to as the Gindikin set. In recent years, varieties of useful extensions of the Wishart distribution have been proposed in the literature for the purposes of studying Markov random fields and graphical models. In particular, generalizations of the Wishart distribution, referred to as Type I and Type II (graphical) Wishart distributions introduced by Letac and Massam in Annals of Statistics (2007) play important roles in both frequentist and Bayesian inference for Gaussian graphical models. These distributions have been especially useful in high-dimensional settings due to the flexibility offered by their multiple-shape parameters. Concerning Type I and Type II Wishart distributions, a conjecture of Letac and Massam concerns the domain of multiple-shape parameters of these distributions. The conjecture also has implications for the existence of Bayes estimators corresponding to these high dimensional priors. The conjecture, which was first posed in the Annals of Statistics, has now been an open problem for about 10 years. In this paper, we give a necessary condition for the Letac and Massam conjecture to hold. More precisely, we prove that if the Letac and Massam conjecture holds on a decomposable graph, then no two separators of the graph can be nested within each other. For this, we analyze Type I and Type II Wishart distributions on appropriate Markov equivalent perfect DAG models and succeed in deriving the aforementioned necessary condition. This condition in particular identifies a class of counterexamples to the conjecture.

David Azriel, Armin Schwartzman.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 174--206.

Abstract:
In this work we study estimation of signals when the number of parameters is much larger than the number of observations. A large body of literature assumes for these kind of problems a sparse structure where most of the parameters are zero or close to zero. When this assumption does not hold, one can focus on low-dimensional functions of the parameter vector. In this work we study one-dimensional linear projections. Specifically, in the context of high-dimensional linear regression, the parameter of interest is ${oldsymbol{eta}}$ and we study estimation of $mathbf{a}^{T}{oldsymbol{eta}}$. We show that $mathbf{a}^{T}hat{oldsymbol{eta}}$, where $hat{oldsymbol{eta}}$ is the least squares estimator, using pseudo-inverse when $p>n$, is minimax and admissible. Thus, for linear projections no regularization or shrinkage is needed. This estimator is easy to analyze and confidence intervals can be constructed. We study a high-dimensional dataset from brain imaging where it is shown that the signal is weak, non-sparse and significantly different from zero.

Ryoya Oda, Hirokazu Yanagihara.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1386--1412.

Abstract:
We put forward a variable selection method for selecting explanatory variables in a normality-assumed multivariate linear regression. It is cumbersome to calculate variable selection criteria for all subsets of explanatory variables when the number of explanatory variables is large. Therefore, we propose a fast and consistent variable selection method based on a generalized $C_{p}$ criterion. The consistency of the method is provided by a high-dimensional asymptotic framework such that the sample size and the sum of the dimensions of response vectors and explanatory vectors divided by the sample size tend to infinity and some positive constant which are less than one, respectively. Through numerical simulations, it is shown that the proposed method has a high probability of selecting the true subset of explanatory variables and is fast under a moderate sample size even when the number of dimensions is large.

Karl Ewald, Ulrike Schneider.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 944--969.

Abstract:
We derive expressions for the finite-sample distribution of the Lasso estimator in the context of a linear regression model in low as well as in high dimensions by exploiting the structure of the optimization problem defining the estimator. In low dimensions, we assume full rank of the regressor matrix and present expressions for the cumulative distribution function as well as the densities of the absolutely continuous parts of the estimator. Our results are presented for the case of normally distributed errors, but do not hinge on this assumption and can easily be generalized. Additionally, we establish an explicit formula for the correspondence between the Lasso and the least-squares estimator. We derive analogous results for the distribution in less explicit form in high dimensions where we make no assumptions on the regressor matrix at all. In this setting, we also investigate the model selection properties of the Lasso and show that possibly only a subset of models might be selected by the estimator, completely independently of the observed response vector. Finally, we present a condition for uniqueness of the estimator that is necessary as well as sufficient.