A Non-parametric Method for Defining a Global Preference Ranking of Industrial Products

Testing and ranking on round-robin design for data sport analytics with application to basketball

By modelling results of sport matches as a set of paired fixed effect linear models, the goal of the present article is showing that traditional scoring outputs can be used to do inference on parameters related to the net relative strength or weakness of teams within a league. As hypothesis testing method, we propose either a normal-based and a non-parametric permutation-based approach. As an extension to round-robin of the ranking methodology recently proposed by Arboretti Giancristofaro et al. (2014) and Corain et al. (2016) , results of pairwise testing are then exploited to provide a ranking of teams within a league. Through an extensive Monte Carlo simulation study, we investigated the properties of the proposed testing and ranking methodology where we proved its validity under different random distributions. In its simplest univariate version, the proposed methodology allows us to infer on the teams average net scoring within a league, while in its more intriguing multivariate layout it is suitable for looking for any team-related global dominance using a wide set of performance indicators. Finally, by using traditional basketball box scores, we present an application to the Italian Basket League.

Measured and perceived environmental comfort: field monitoring in an Italian school

Microclimatic conditions were recorded in an Italian school and Fanger's indexes PMV and PPD were calculated under different conditions. Students' sensations were investigated four times by means of two surveys, one related to actual microclimatic conditions and one on overall satisfaction, interaction occupant-building and reactions to discomfort. Pupils' classroom position was considered to look for possible influence on thermal comfort: a difference emerged from PMV and the survey, but the results obtained from the two approaches differ for both the entity of discomfort and its distribution within each classroom. Innovative multivariate nonparametric statistical techniques were applied to compare and rank the classrooms in accordance with students' subjective perceptions; a global ranking has been also calculated, considering thermal and visual comfort and air quality. Comparing pupil-sensation-based ranking with environmental parameters no clear correspondence was found, except for mid-season, where PMV, CO2 concentration and desk illuminance were similar in all the classrooms.