Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.


Slicing Public Opinion for State and National Research

In this paper, we develop and release measures of public ideology in 2010 for the 50 American states, 435 congressional districts, and state legislative districts. We do this using the geospatial statistical technique of kriging, which uses the locations of survey respondents, as well as population covariate values, to predict ideology for simulated citizens in districts across the country. In doing this, we improve on past research …


On Surrogate Variable Analysis for High Dimensional Genetics and Genomics Data

Unwanted variation in hidden variables often negatively impacts analysis of high-dimensional data, leading to high false discovery rates, and/or low rates of true discoveries.  A number of procedures have been proposed to detect and estimate the hidden variables, including principal component analysis (PCA).  However, empirical data analysis suggests that PCA is not efficient in identifying the hidden…


Confidence Inference Function in Big Data

Statistical inference along with the strategy of divide-and-combine for Big Data analysis has been little studied.  As an effective inferential tool, confidence distribution (CD) has attracted a surge of renewed attention. The essence in constructing confidence distribution pertains to the availability of suitable pivotal quantities, which are usually obtained from the (asymptotical) distribution of point maximum…


Functional and very high dimension reduction

The talk has two components. In the first component, to study the relation between a univariate response and multiple functional covariates, we propose a functional single index model that is semiparametric. The parametric part of the model integrates the linear regression modeling for functional data and the sucient dimension reduction structure. The nonparametric part of the model further allows the response-index dependence or the link…


Visualizing chance in introductory probability

Research in the last thirty years has documented the challenges and difficulties in teaching probability and the many misconceptions prevalent in people’s reasoning. There is now a call to reform the approach to teaching probability from a traditional mathematical base to include more emphasis on modeling andinvestigations. Within this spirit of reform we undertook a two-part exploratory study. In the first part we interviewed seven…


Design of Experiments: From Small Data to Big Data

Experimentation is an integral part of science. Exploring or analyzing data leads to new insights, hypotheses, and questions that fuel further investigation. Before data can be explored or analyzed, it needs to be collected. Where possible, this is ideally done through a designed experiment. In a designed experiment, conditions under which observations are made can be controlled, and causal relationships can be studied. A central question in…


Revenue Forecasting in Technological Services: Evidence from Large Data Centers

Data Center is a facility, which houses computer systems and associated components, such as telecommunications and storage systems. It generally includes power supply equipment, communication connections, and cooling equipment. A large data center can use as much electricity as a small town. The emergence of data-center based computing services necessitates the examination of the costs associated with such data centers and the evolution of such…


Modeling and Analysis of Inherently Complex-Valued FMRI Data

In fMRI and fcMRI, the original data measured by the MRI machine are complex-valued, a complex-valued inverse Fourier transform is applied to reconstruct into a complex-valued image. Almost exclusively, the Cartesian real and imaginary images are converted to magnitude and phase images, then the phase half of the data is discarded before statistical analysis. A description of potential biological information in the phase will be provided along…


Richard Ross and Yan Wang


Adaptive Designs for Population Enrichment Strategy

Population enrichment strategy offers a specific adaptive design methodology to study the effect of experimental treatments in various sub-populations of patients under investigation.  Instead of limiting the enrollment only to the enriched population, these designs enable the data-driven selection of one or more pre-specified subpopulations at an interim analysis and the confirmatory proof of efficacy in the selected subset at the end of…
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