Franklin Pierce Law Center: Leading the Way in Legal Education for New Hampshire

[Excerpt] This issue of the Pierce Law Review is the first devoted entirely to the practice of law in New Hampshire. This venture is appropriate because the Franklin Pierce Law Center is the only law school in the State. We are truly New Hampshire’s law school. Our Trustees, faculty, staff, and students feel this responsibility profoundly. Pierce Law serves as both a state law school and a national and international school. While we send a greater percentage of our graduates out of state than any other law school in the country except one, our alumni comprise fully one-third of the lawyers in New Hampshire. (I should point out, too, that we have almost one thousand alumni in over one hundred countries.

A sequential test procedure for monitoring a singular safety and efficacy outcome

In this note we describe a modification of the sequential probability ratio test (SPRT) developed for the purpose of “flagging” a significant increase in the mortality rate of a treatment relative to a control while ensuring that double-blinding and the Type I error for the primary test of efficacy, also based on mortality rates, is not compromised. Key words: Interim analysis; safety monitoring; sequential testing. Trop J Pharm Res, December 2003; 2(2): 197-20

Functional design for operational earth resources ground data processing

The author has identified the following significant results. Study emphasis was on developing a unified concept for the required ground system, capable of handling data from all viable acquisition platforms and sensor groupings envisaged as supporting operational earth survey programs. The platforms considered include both manned and unmanned spacecraft in near earth orbit, and continued use of low and high altitude aircraft. The sensor systems include both imaging and nonimaging devices, operated both passively and actively, from the ultraviolet to the microwave regions of the electromagnetic spectrum

Reducing the Effects of Unequal Number of Games on Rankings

Ranking is an important mathematical process in a variety of contexts such as information retrieval, sports and business. Sports ranking methods can be applied both in and beyond the context of athletics. In both settings, once the concept of a game has been defined, teams (or individuals) accumulate wins, losses, and ties, which are then factored into the ranking computation. Many settings involve an unequal number of games between competitors. This paper demonstrates how to adapt two sports rankings methods, the Colley and Massey ranking methods, to settings where an unequal number of games are played between the teams. In such settings, the standard derivations of the methods can produce nonsensical rankings. This paper introduces the idea of including a super-user into the rankings and considers the effect of this fictitious player on the ratings. We apply such techniques to rank batters and pitchers in Major League baseball, professional tennis players, and participants in a free online social game. The ideas introduced in this paper can further the scope that such methods are applied and the depth of insight they offer

A Characterization of Most(More) Powerful Test Statistics with Simple Nonparametric Applications

Data-driven most powerful tests are statistical hypothesis decision-making tools that deliver the greatest power against a fixed null hypothesis among all corresponding data-based tests of a given size. When the underlying data distributions are known, the likelihood ratio principle can be applied to conduct most powerful tests. Reversing this notion, we consider the following questions. (a) Assuming a test statistic, say T, is given, how can we transform T to improve the power of the test? (b) Can T be used to generate the most powerful test? (c) How does one compare test statistics with respect to an attribute of the desired most powerful decision-making procedure? To examine these questions, we propose one-to-one mapping of the term 'Most Powerful' to the distribution properties of a given test statistic via matching characterization. This form of characterization has practical applicability and aligns well with the general principle of sufficiency. Findings indicate that to improve a given test, we can employ relevant ancillary statistics that do not have changes in their distributions with respect to tested hypotheses. As an example, the present method is illustrated by modifying the usual t-test under nonparametric settings. Numerical studies based on generated data and a real-data set confirm that the proposed approach can be useful in practice.Comment: Accepte