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Past Seminars in Spring 2013:

The Role of Predictive Distributions in Process Optimization

Speaker: John J. Peterson, Quantitative Sciences Department,GlaxoSmithKline Pharmaceuticals

Abstract:

Quality improvement has been described in a nutshell as "reduction in variation about a target". Such reduction is driven by the desire to have a high probability of meeting process specifications. However, many statistical quantifications and decisions related to process optimization and response surface analyses are focused only on means, without careful thought to the role of variation and risk assessment. A focus on inference for means is also evident from a review of classical response surface methodology textbooks and popular statistical packages for process optimization. This has caused many scientists and engineers to ignore careful modeling of key sources of variation and to propose regions of process operation that are far too large, thereby harboring process operating conditions associated with poor process performance. This talk will illustrate some of the dangers of failing to account for process variation properly. It will also show how predictive distributions can be used for better process optimization.

Friday, April 19th 11:00 AM - 12:00 PM

Location: Duques 151 (2201 G Street, NW))


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Vast Search Affect

Speaker: Gerhard Pilcher, Vice President and Senior Scientist, Elder Research Inc.

Abstract:

The American public is often confronted with sensationalized studies that show statistically significant results for one new phenomenon or another. For example, you might read a headline such as this: "Mother's Depression Linked to Child's Shorter Height," ABC News, Sept 10, 2012. The headline is flashy enough to grab attention. But a new level of truth becomes apparent when one takes the time to learn how the study was designed and how the information was analyzed.

Studies such as this tend to suffer from Vast Search Effect, affectionately called data dredging at Elder Research, Inc. If an analyst conducts continuous analysis of one aspect of data without reflecting on other contributing factors, some kind of relationship in the data is likely to be "discovered." The result may be a random occurrence in the particular sample of data analyzed or may not actually be the most interesting insight contained in the data. Vast Search Effect is the reason why the public hears conflicting messages, such as coffee is good for you ... no, coffee causes a certain type of cancer and hypertension ... ooops, actually now coffee is good for you again. These contradictory conclusions cause confusion and weaken people's confidence in studies and analytics in general.

Please join Elder Research, Inc. in the discussion of Vast Search Effect. The outcome of our discussion is to create a healthy skepticism for the most promising data discoveries, which should then motivate us to consider the boundary between data mining and data dredging in our own analysis. ERI will discuss how to recognize data dredging using a recent example covered in the press.

Friday, April 12th 11:00 AM - 12:00 PM

Location: Duques 651 (2201 G Street, NW))


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Quality of Target Benefits of Proposed Projects: Developing a Generic Construct

Speaker: Dr. Ofer Zwikael - Australian National University

Abstract:

Organizational growth is accelerated by successful implementation of projects, hence project selecting and funding are critical organizational decisions. While literature is comprehensive in its discussion on financial analysis of proposed projects, it is weaker when it comes to assessment of non-financial target benefits, those anticipated to be realized after project completion. Consequently, target benefits of proposed projects are often vaguely defined, inflated, and suffer from optimism bias. Based on findings from two studies, this seminar specifies a new construct for assessing anticipated non-financial benefits, entitled "quality of target benefits" (QTB), develops and validate a generic scale for its measurement, consisting of seven dimensions: relevance, specificity, measurability, time frame, achievability, accountability, and comprehensiveness. These dimensions extend goal-setting theory to the project context. Research findings show that QTB improves the quality of project funding decisions. The construct can lead to more informed and justifiable project funding decisions in organizations. It contributes to the literature by providing an instrument to facilitate theory development research on organizational strategy implementation, decision making and project performance evaluation.

Friday, April 5th 11:00 AM - 12:00 PM

Location: Duques 453 (2201 G Street, NW))


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Should Event Organizers Prevent Resale of Tickets ?

Speaker: Ozge Sahin, Carey Business School, Johns Hopkins University

Abstract:

We are interested in whether preventing resale of tickets benefits the capacity providers for sporting and entertainment events. Common wisdom suggests that ticket resale is harmful to event organizers' revenues and event organizers have tried to prevent resale of tickets. For instance, Ticketmaster has recently proposed paperless (non-transferrable) ticketing which would severely limit the opportunity to resell tickets. Surprisingly, we find that this wisdom is incorrect when event organizers use fixed pricing policies, in fact event organizers benefit from reductions in consumers' (and speculators') transaction costs of resale. Even when multi-period pricing policies are used, we find that an event organizer may still benefit from ticket resale if his capacity is small. Given that limiting ticket resale by making it more difficult has resulted in adverse consumer reactions, we propose a novel ticket pricing mechanism of ticket options. We show that ticket options (where consumers would initially buy an option to buy a ticket and then execute at a later date) naturally result in reducing ticket resale significantly and result in significant increases in event organizers' revenues. Furthermore, since a consumer only risks the option price (and not the whole ticket price) if she cannot attend the event, options may face less consumer resistance than paperless tickets. (This is joint work with Yao Cui and Izak Duenyas).

Friday, March 29th 11:00 AM - 12:00 PM

Location: Duques 553 (2201 G Street, NW))


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Adversarial Risk Analysis: Games and Auctions

Speaker: David Banks, Department of Statistical Science Duke University

Abstract:

Adversarial risk analysis is a decision-analytic approach to strategic games. It builds a Bayesian model for the solution concept, goals, and resources of the opponent, and the analyst can then make the choice that maximizes expected utility against that model. Adversarial risk analysis operationalizes the perspective in Kadane and Larkey (1982), and it often enables the analyst to incorporate empirical data from behavioral game theory. The methodology is illustrated in the context of Le Relance, a routing game, and auctions

Friday, March 1st, 11:00 AM - 12:15 PM

Location: Duques 651 (2201 G Street, NW)


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Cholesky Stochastic Volatility Models for High-Dimensional Time Series

Speaker: Dr. Hedibert Lopes, Associate Professor of Econometrics and Statistics, University of Chicago Booth School of Business

Abstract:

Multivariate time-varying volatility has many important applications in finance, including asset allocation and risk management. Estimating multivariate volatility, however, is not straightforward because of two major difficulties. The first difficulty is the curse of dimensionality. For p time series, there are p(p+1)/2 volatility and cross-correlation series. The second difficulty is that the conditional covariance matrix must be positive definite for all time points. This is not easy to maintain when the dimension is high. In order to simply maintain positive definiteness, we model the Cholesky root of the time varying p x p covariance matrix. Our modeling approach is chosen to allow for parallel computation and we show how to optimally distribute the computations across processors. We illustrate our approach by a number of real and synthetic examples, including a real application with 94 components (p=94) of the S&P 100 index. This is joint work with Robert McCulloch (University of Chicago) and Ruey Tsay (University of Chicago).

Friday, February 22nd, 11:00 AM - 12:00 PM

Location: Duques 553 (2201 G Street, NW)


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Next Generation of Mathematical Programming Modeling and Solving Tools

Speaker: Dr. Alkis Vazacopoulos, CEO Industrial Algorithms

Abstract:

During the last 40 years Mathematical Programming (MP) has increasingly found applications in industry in various areas such as finance, marketing, supply chain, energy, data mining and decision analytics. MP optimization has benefited thousands of companies in the USA and abroad and produces savings of billions of dollars. Ongoing developments in the technology are making MP more widely accepted by businesses worldwide. This talk reviews the current state of the art of MP in view of recent developments. Historically, modeling mathematical programming problems has relied on either of two methodologies. The first methodology is the creation of the matrix and the import to a mathematical programming solver. The second common methodology is the use of an algebraic modeling language which will produce the corresponding matrix and will manage the solving by passing it to a solver also. A new methodology which creates both the algebra and the matrix as well as passing it to a third party solver is done using a flowsheet or network based interface. This methodology minimizes the need for domain specific knowledge in terms of writing the sets, parameters, variables and constraints of the model making for easier implementation of MP in practice. This new technology can be applied to both horizontal and vertical markets such as finance (wealth management), marketing optimization, supply chain planning, refinery planning and scheduling, energy/co-generation optimization, maintenance turnaround programming, production accounting/data reconciliation problems. The speaker will address questions about how today's companies can implement the next generation of mathematical programming and the benefits they can accrue from it.

Friday, February 15th, 11:00 AM - 12:15 PM

Location: Duques 453 (2201 G Street, NW)


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Big Data Revolution: Analytics and Optimization

Speaker: Dr. Alkis Vazacopoulos, CEO Industrial Algorithms

Abstract:

How do companies define Big Data? How are they using it? What strengths are they receiving from Big Data Analytics? We will review what Big Data means, and we will explore case studies from Banking, Insurance, Retail and Healthcare Verticals.

Thursday, Feburary 14th, 7:10 PM - 8:15 PM

Location: Duques 651 (2201 G Street, NW)


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Stable Distributions: Models for Heavy Tailed data

Speaker: John Nolan, American University, Washington, D.C

Abstract:

Stable distributions are a class of heavy tailed probability distributions that generalize the Gaussian distribution and that can be used to model a variety of problems. An overview of univariate stable laws is given, with emphasis on the practical aspects of working with stable distributions. Then a range of statistical applications will be explored. If there is time, a brief introduction to multivariate stable distributions will be given.

Friday, January 25th, 3:30 PM - 4:30 PM

Location: Duques 553 (2201 G Street, NW)


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Introduction to R: modeling, computing, visualizing and fun

Speaker: Shivraj Kanungo, Department of Decision Sciences, The George Washington University

Abstract:

The use of the R environment for statistical computing and data analysis has exploded over the last decade and R has matured into a mainstream and must-know environment that every serious (and fun loving!) academic should leverage. Given its unrivalled advantages in terms of access, help, flexibility, extensibility and aesthetics, my presentation will showcase the salient features of R so as to provide you with a working knowledge of R. I have planned to deliver this interactive presentation in three parts. Part 1 will consist of: a brief introduction to R, an interactive R session, and an introduction to both the command line as well as GUI-based interactive frameworks for R. Part 2 will cover: data types and file and data handling, the use of packages in R, a session on basic inferential statistics (t-tests, ANOVA, ANCOVA, MANOVA and regression) and R graphics. In Part 3 I will attempt to convey the breadth of R and will present and demonstrate three topics briefly: network analysis, optimization and simulation. I will close by showing how easy it is to install and maintain R. Time-permitting, I will briefly show how I have used R in my research. By the way, R has a well-developed package for handling qualitative (i.e. textual, interview-based) data.

Friday, January 25th, 11:00 AM - 12:30 PM

Location: Duques 553 (2201 G Street, NW)