G. Rex Bryce

The Effect of Depth Jumps and Weight Training on Leg Strength and Vertical Jump

Abstract In recent years, a method of plyometrics (exercises that cause a rapid lengthening of a muscle prior to contraction) called depth jumping has become a part of the training routine of many athletes. Two experiments are described in which the effectiveness of the exercises is examined. In Experiment 1, undergraduate students in beginning weight training classes trained with three different jumping programs: (1) maximum vertical jumps, (2) 0.3 m depth jumps, and (3) 0.75 m and 1.10 m depth jumps. In addition, all groups also lifted weights. In Experiment 2, a weight training class and the volleyball team at Brigham Young University-Hawaii were divided into two groups. One group lifted weights and performed 0.75 and 1.10 m depth jumps. The other group only lifted weights. In Experiment 1, the three training programs resulted in increases in one repetition maximum (1 RM) squat strength, isometric knee extension strength, and in vertical jump; however, there were no significant differences between trea...

Design issues for adaptive control charts

Adaptive control charts allow the components of the quality-monitoring scheme to vary in order to obtain improved performance over non-adaptive control charts. Research has centered on components such as the sample size, time between samples, warning limits, and control limits and has recommended a variety of schemes, many of which are optimal in some sense. In practice, there are many other adaptive schemes that are near optimal, which will still yield considerable improvement over non-adaptive control charts. In addition, the impact of parameter estimation on adaptive control chart performance must be taken into consideration. Based on the simulation results shown here, adaptive control charts should only be used for mature processes, where a sufficient amount of Phase I data have been obtained to ensure that the estimated control limits are accurate. When evaluating control chart performance, we consider initial state performance measures for simplicity and note that the conclusions obtained here apply to steady-state performance measures. The evaluation of performance measures is easily handled by the Markov chain approach detailed in the Appendix. Copyright

Correspondence between a Linear Restriction and a Generalized Inverse in Linear Model Analysis

Abstract In experimental statistics the usual method of estimating treatment effects is to introduce arbitrary linear restrictions among the treatment effects in order to obtain solutions of the normal equations. A comparatively recent approach is to dispense with the linear restriction and use a generalized inverse solution to the normal equations. The present note is an attempt to bring these two methods closer together and show their correspondence; namely, for each given linear restriction, there exists a corresponding generalized inverse that yields the same solution for the treatment effects as the linear restriction does.

Developing Tomorrow's Statisticians.

Many leaders of our profession have called for improvements in the way we educate statisticians. Sound recommendations have been made by many, based on real-world experience in the practice of statistical science. These calls for reform have gone largely unheeded, at least in part because of our current paradigm of statistical education. Statistics is seen, by many, as strictly a graduate discipline, yet constraints on the time to complete a graduate degree makes adopting many of the reforms that have been suggested very difficult. It is argued in this paper that a new paradigm of statistical education is needed that provides for strong undergraduate programs in statistics. Such programs would give the profession wider recognition and provide additional entries into the discipline.

Undergraduate Statistics Education: An Introduction and Review of Selected Literature

A recent symposium on “Improving the Work Force of the Future: Opportunities in Undergraduate Statistics Education” was held to focus attention on the importance of undergraduate statistics education. The symposium and the approval of curriculum guidelines for undergraduate degrees by the Board of Directors of the American Statistical Association have done much to define the current state of undergraduate education in statistics and suggest directions for improvement. This article summarizes the activities leading up to the symposium and provides a brief summary of six papers from the symposium that have been published. The article concludes with a discussion of some of the outstanding issues that remain to be addressed.

Estimating the Standard Deviation for Individuals Control Charts

We address the issue of which estimate of the standard deviation should be used in calculating control limits for an individuals control chart. Four possible estimators of the standard deviation of the underlying common-cause process are considered: the..

Estimation and hypothesis in linear models-A reparameterization approach to the cell mlans modll

A general approach to analysis of fixed effects models through a reparameterization of the cell means model is outlined. After applying a Q-op3rator, distribution theory for the model is developed. Methods of estimation and hypothesis testing are given and the exact form of each hypothesis is shown. The implementation of these results in a currently available computer package is discussed.

Control Limits for Group Charts

An application of group charts to a multiple filling head bottling machine at the BYU Creamery motivated an investigation of in-control average run length (ARL). It is shown that ARL of an in-control process with k streams is approximately 370/k. This..

Orthogonalization-Triangularization Methods in Statistical Computations

Abstract Procedures are presented for reducing a data matrix to triangular form by using orthogonal transformations. It is shown how an analysis of variance can be constructed from the triangular reduction of the data matrix. Procedures for calculating sums of squares, degrees of freedom, and expected mean squares are presented. It is demonstrated that all statistics needed for inference on linear combinations of parameters of a linear model may be calculated from the triangular reduction of the data matrix.

Latin square changeover design in physical education research.

Abstract The Latin square changeover design, which may be applied to the study of physiological parameters, is investigated. The utility of the design in relation to identifying and estimating residual treatment effects is discussed, with an example of an application of the design. The example involves a caloric cost study in which each subject receives six different treatments. Therefore, the possibility of carry-over effects is considered. Analysis techniques are discussed, including problems related to the confounding of effects resulting from the designs nonorthogonality. The magnitudes of the carry-over effects are calculated. Finally, the design is compared to the randomized block and Latin square designs, and the relative efficiency of the changeover design is demonstrated.