We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

Motivated by the desire to support the installation of a new computer system, to determine the optimum method of training novice computer users, and to assess learning style’s role in computing system training, this study used structural equation modeling to examine and understand the results of a field experiment. Four hundred and fifty members of the U.S. Navy were studied using three training methods: (1) instruction, (2) exploration, and (3) behavior modeling. Trainees ’ learning style was determined using Kolb’s Learning Styles Inventory. The results of the analysis indicate that trainees whose learning style matched training methodology were more successful in training outcomes, had higher computing satisfaction, and had higher levels of computer use. The results showed that behavior modeling trainees were not influenced by learning style and these trainees had the highest levels of satisfaction and computer use. Forty percent of the respondents to a National Association of Manufacturers survey reported having serious problems upgrading their company’s technology because of a lack of employee skills

Speed-to-Market is cited as being vital in today’s competitive, uncertain and turbulent environments. Scholars and industry professionals alike assert that companies can achieve competitive advantages by launching their product faster than their competitors. However, this paper presents a slightly different perspective on speed-to-market by considering another aspect of the speed equation-speed-to-learn or fast learning in new product development (NPD) teams. We assert that although speed-to-market can increase the probability of new product success, speed-to-learn is one of the critical factors that allows teams to get to market rapidly and be more successful. In this study, we propose a model for fast team learning in new product development based on constructs borrowed from accelerated learning models or suggestopedy in the individual learning scholarship. We then empirically test the model on 171 new product teams. We argue that 1) fastlearning teams launch new products quicker with an increased probability of success. And 2) specific mechanisms that are within the teams ’ control can help teams learn faster. Mechanisms uncovered include: vision clarity, learning from customer and competitor, and information coding.

As the Web becomes a part of peoples ’ everyday lives, there is a growing need to understand user behaviour on the Web. Recently, the flow construct has been proposed as important for understanding the nature of user online experience. Researchers assert that the benefits of flow online include increased learning, exploratory and positive behavior, positive subjective experience, and perceived sense of control over their interaction. Overall, flow could affect outcomes such as navigation patterns and repeat visits on commercial Web sites. Although widely studied over the past years, a review of the literature indicates discrepancies among various flow models and some unclear conceptualization and operationalization of the construct. This paper examined flow according to two specific conceptualizations with respect to its measurement, and tests each conceptualization in an identical nomological network. The results indicate that there is better fit of a reflective flow model compared with a formative flow model to the study data. The results of the study may aid in the understanding of the relationships between the higher order flow construct and its first order dimensions, which may help inform system designers to better assess flow and, thus, be more conducive to flow. Keywords: Computer-Mediated Environment, Flow, Multidimensionality, Web 1.

The views expressed in this report are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of the following information A great deal of information on the European Union is available on the Internet.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Copyright 2005, UPA. Vol. 2, Issue 1, November 2006, pp. 39-53 This study was a follow-up to determine the psychometric quality of the usability questionnaire items derived from a previous study (Ryu and Smith-Jackson, 2005), and to find a subset of items that represents a higher measure of reliability and validity. To evaluate the items, the questionnaire was administered to a representative sample involving approximately 300 participants. The findings revealed a six-factor structure, including (1) Ease of learning and use, (2) Assistance with operation and problem solving, (3) Emotional aspect and multimedia capabilities, (4) Commands and minimal memory load, (5) Efficiency and control, and (6) Typical tasks for mobile phones. The appropriate 72 items constituted the Mobile Phone Usability Questionnaire (MPUQ), which evaluates the usability of mobile phones for the purpose of making decisions among competing variations in the end-user market, determining alternatives of prototypes during the development process, and evolving versions during an iterative design process. Keywords usability, mobile user interface, questionnaire, reliability, validity

Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) are both variable reduction techniques and sometimes mistaken as the same statistical method. However, there are distinct differences between PCA and EFA. Similarities and differences between PCA and EFA will be examined. Examples of PCA and EFA with PRINCOMP and FACTOR will be illustrated and discussed.

Data mining has captured the hearts and minds of business analysts seeking a solution for exploring and modeling vastly larger, more complex and less well-behaved datasets. Exploratory data analysis, typically consisting of activities like statistical visualization, hypothesis generation, and introductory model fitting is a vital first step in any successful data mining venture. Exploratory data analysis produces direct benefits for data miners in enhanced understanding of data, improved clarity and confidence of the modeling results, and avoidance of pitfalls early in the process. SAS/INSIGHT is SAS Institute's leading software for facilitating exploratory data analysis featuring a uniquely visual analytic toolset. This paper will review the usefulness of SAS/INSIGHT software for exploratory data analysis, interactive regression modeling, and advanced multidimensional data visualization. Along the way, we'll explore how to win baseball games and still save enough money to build the s...

As advances in technology permit manufacturing ICs with millions of transistors, testing complexity increases. Inaccuracies in fault-models, new defect mechanisms and the lack of complete understanding of physical defect mechanisms render use of existing test methods in isolation obsolete. To distinguish between faulty and fault-free chips and identify outliers it is necessary to correlate test parameters. Use of multiple parameter-based testing, with specific focus on use of leakage current (I DDQ ) measurement, is proposed. It is necessary to use statistical methods in combination with these methods. With escalating cost and reduced effectiveness, alternatives to burn-in testing are continuously sought. Identifying outliers can help semiconductor manufacturers reduce or eliminate burn-in. This can result in a dramatic reduction in test cost. A possible application of this research for burn-in and test cost reduction is discussed.

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