Book Reviews

Open Access: Key Strategic, Technical and Economic Aspects Edited by Neil Jacobs Chandos Publishing, 2006. 250 pp. ISBN 1‐84334‐203‐0, £39.95, pbk ISBN 1‐84334‐204‐9, £57.00, hbk Selling Rights, 5th edn Lynette Owen Routledge, 2006. 384 pp. ISBN 978‐0‐415‐36280‐1, £75.00 hbk ISBN 978‐0‐415‐38652‐4, £29.95 pbk Bound by Law? Tales from the Public Domain by Keith Aoki, James Boyle and Jennifer Jenkins Duke Law School Center for the Study of the Public Domain, 2006. 76 pp. ISBN 0‐974‐15531‐4, $5.95, pbk. Freely available online at http://www.law.duke.edu/cspd Digital Preservation Marilyn Deegan Simon Tanner Facet Publishing, 2006, Digital Futures Series. 288 pp. ISBN 978‐1‐85604‐485‐1, £39.95, hbk.     

Statistical methods for analysing discrete and categorical data recorded in performance analysis

In this paper, we identify appropriate statistical methods for analysing categorical differences in discrete variables or 'performance indicators' resulting from performance analysis. The random mechanisms associated with discrete events do not follow a normal distribution; that is, the normal distribution is a continuous not a discrete probability distribution. We propose appropriate statistical methods based on two key discrete probability distributions, the Poisson and binomial distributions. Two approaches are proposed and compared using examples from notational analysis. The first approach is based on the classic chi-square test of significance (both the goodness-of-fit test and the test of independence). The second approach adopts a more contemporary method based on log-linear and logit models fitted using the statistical software GLIM. Provided relatively simple one-way and two-way comparisons in categorical data are required, both of these approaches result in very similar conclusions. However, as soon as more complex models or higher-order comparisons are required, the approach based on log-linear and logit models is shown to be more effective. Indeed, when investigating those factors and categorical differences associated with binomial or binary response variables, such as the proportion of winners when attempting decisive shots in squash or the proportion of goals scored from all shots in association football, logit models become the only realistic method available. By applying log-linear and logit models to discrete events resulting from notational analysis, greater insight into the underlying mechanisms associated with sport performance can be achieved.     

Prediction of maximum oxygen consumption from walking, jogging, or running

The purpose of this study was to develop a submaximal, 1.5-mile endurance test for college-aged students using walking, jogging, or running exercise. College students (N = 101: 52 men, 47 women), ages 18-26years, successfully completed the 1.5-mile test twice, and a maximal graded exercise test. Participants were instructed to achieve a "somewhat hard" exercise intensity (rating of perceived exertion = 13) and maintain a steady pace throughout each 1.5-mile test. Multiple linear regression generated the following prediction equation: VO2 max = 65.404 + 7.707 x gender (1 = male; 0 =female) - 0.159 x body mass (kg) - 0.843 x elapsed exercise time (min; walking, jogging orrunning). This equation shows acceptable validity (R = .86, SEE = 3.37 ml x kg(-1) min(-1)) similar to the accuracy of comparable field tests, and reliability (ICC = .93) is also comparable to similar models. The statistical shrinkage is minimal (R(press) = 0.85, SEE(press) = 3.51 ml x kg(-) x min(-1)); hence, it should provide comparable results when applied to other similar samples. A regression model (R =.90, and SEE = 2.87 ml x kg(-1) min(-1)) including exercise heart rate was also developed: VO2 max = 100.162 +/- 7.301 x gender(1 = male; 0 =female) - 0.164 x body mass (kg) - 1.273 x elapsed exercise time -0.156 x exercise heart rate, for those who have access to electronic heart rate monitors. This submaximal 1.5-mile test accurately predicts maximal oxygen uptake (VO2max) without measuring heart rate and is similar to the 1.5-mile run in that it allowsfor mass testing and requires only a flat, measured distance and a stopwatch. Further, it can accommodate a wide range of fitness levels (from walkers to runners).