Accessing Social Statistics

published or submitted for publicatio

The Foundation Performance Dashboard: Vital Statistics for Social Impact

Boards and foundation leadership rarely have a clear, consistent, and comprehensive picture of their foundation's performance. Interestingly, this situation persists despite the fact that nearly 60% of foundation CEOs would like to have more board involvement in reviewing the foundation's philanthropic mission and effectiveness. Our experience suggests that this conundrum results from a fundamental uncertainty: Foundations are unsure how to bridge the chasm between the readily available and concise metrics for investment performance and the much more complex, expensive, and subjective data from internal operations and program evaluations

Robust Statistics

In lieu of an abstract, here is the entry\u27s first paragraph: Robust statistics are procedures that maintain nominal Type I error rates and statistical power in the presence of violations of the assumptions that underpin parametric inferential statistics. Since George Box coined the term in 1953, research on robust statistics has centered on the assumption of normality, although the violation of other parametric assumptions (e.g., homogeneity of variance) has their own implications for the accuracy of parametric procedures. This entry looks at the importance of robust statistics in educational and social science research and explains the robustness argument. It then describes robust descriptive statistics, their inferential extensions, and two common resampling procedures that are robust alternatives to classic parametric methods

Domain general learning: Infants use social and non-social cues when learning object statistics.

Previous research has shown that infants can learn from social cues. But is a social cue more effective at directing learning than a non-social cue? This study investigated whether 9-month-old infants (N = 55) could learn a visual statistical regularity in the presence of a distracting visual sequence when attention was directed by either a social cue (a person) or a non-social cue (a rectangle). The results show that both social and non-social cues can guide infants' attention to a visual shape sequence (and away from a distracting sequence). The social cue more effectively directed attention than the non-social cue during the familiarization phase, but the social cue did not result in significantly stronger learning than the non-social cue. The findings suggest that domain general attention mechanisms allow for the comparable learning seen in both conditions

A mixed effects model for longitudinal relational and network data, with applications to international trade and conflict

The focus of this paper is an approach to the modeling of longitudinal social network or relational data. Such data arise from measurements on pairs of objects or actors made at regular temporal intervals, resulting in a social network for each point in time. In this article we represent the network and temporal dependencies with a random effects model, resulting in a stochastic process defined by a set of stationary covariance matrices. Our approach builds upon the social relations models of Warner, Kenny and Stoto [Journal of Personality and Social Psychology 37 (1979) 1742--1757] and Gill and Swartz [Canad. J. Statist. 29 (2001) 321--331] and allows for an intra- and inter-temporal representation of network structures. We apply the methodology to two longitudinal data sets: international trade (continuous response) and militarized interstate disputes (binary response).Comment: Published in at http://dx.doi.org/10.1214/10-AOAS403 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Building an Open Social Learning Community Around a DSpace Repository on Statistics

4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PostersIn this paper we describe a project which aims to build an open social learning community around a learning object repository (LOR) based on DSpace containing learning resources about Statistics. We combine the preservation capabilities of DSpace with the facilities of a tagging mechanism such as Delicious. On top of this ensemble we intend to build a new browsing interface for improving users' learning experience when using the LOR. We also intend to gather and analyze usage data in order to better understand the real learning process in virtual learning environments.Spanish Government Grant under Refs. TIN2006-15107-C06 and EA2008-015

Tenement House Conditions in Five Rhode Island Cities

George H. Webb, Commissioner. Carol Aronovici, Special Agent. Rhode Island Bureau of Industrial Statistics. Part I of the Annual Report for 1910. A report commissioned by the Rhode Island Bureau of Industrial Statistics conducted in cooperation with the Rhode Island Bureau of Social Research, an agency of the Union for Christian Work, which examined the tenement housing conditions found in Providence, Pawtucket, Central Falls, Woonsocket, and Newport, RI.https://digitalcommons.providence.edu/ri_history/1017/thumbnail.jp