College of Liberal Arts & Sciences

# Hogg and Craig Lectures

When the Department of Statistics and Actuarial Science was created in 1965, it had 5 faculty members: Bob Hogg, Allen Craig, John Birch, Lloyd Knowler, and Jim Hickman. Hogg was the founding chair of the department.

Craig, who earned his UI PhD in 1931, was the doctoral advisor of Hogg, who earned his UI PhD in 1950. By then, Craig had already made important contributions to the profession. Indeed, he was instrumental in getting the Institute of Mathematical Statistics started and was on the original (1938) editorial board of the IMS’s Annals of Mathematical Statistics, along with Jerzy Neyman and Sam Wilks (UI PhD 1931). Hogg would go on to make important contributions of his own, serving as program secretary for the IMS from 1968-1974 and president of the American Statistical Association in 1988.

Hogg and Craig had different personalities but shared many of the same passions. They both loved statistics and they both were terrific scholars and educators. They teamed up in 1958 to write one of the most popular mathematical statistics books ever written – the book known eponymously as “Hogg and Craig.”

The annual Craig Lectures began when Allen Craig delivered his retirement talk in 1970. In the following years, Craig Lectures included Fred Mosteller, Brad Efron, Bob Hogg, Jim Hickman, Carl Morris, Herman Chernoff, Luke Tierney, and Alan Agresti. When Bob Hogg passed away in 2014, the lectures were renamed the Hogg and Craig Lectures. Past Hogg and Craig Lecturers include Dick Dykstra, Xiao-Li Meng, David Donoho, and Donald Rubin.

**Lecture #50 - April 28 and 29, 2023**

Dan Nettleton, Iowa State University, "My Adventures in Sports Statistics, Beginning With Bob Hogg" and "Who Is Winning? Determining Whether a Candidate Leads in a Ranked-Choice Election"

More information can be found here.

**Lecture #49 - 2022**

Donald B. Rubin, Harvard University, "Essential Concepts of Causal Inference: A Remarkable History and an Intriguing Future” and “Conditional Calibration and the Sage Statistician”

More information can be found here.

**Lecture #48 - 2021**

Bin Yu, University of California at Berkeley, "Veridical Data Science: the practice of responsible data analysis and decision-making” and “Iterative Random Forests (iRF) with applications to biomedical problems through epiTree for epistasis discovery”

More information can be found here.

**Lecture #47 - 2019**

David A. Harville, Iowa State University, "Ranking/Rating Basketball or Football Teams: the NCAA Way and the ‘Right’ Way” and “Model-Based Prediction in General and in the Special Case of Ordinal Data”

More information can be found here.

**Lecture #46 - 2018**

David Donoho, Stanford University, "50 Years of Data Science” and “Covariance Estimation in Light of the Spiked Covariance Model”

More information can be found here.

**Lecture #45 - 2017**

Xiao-Li Meng, Harvard University, "From Euler to Clinton: An Unexpected Statistical Journey (Or: Size Does Matter, but You Might be in for a Surprise…)” and “Bayesian, Fiducial, and Frequentist (BFF): Best Friends Forever?”

More information can be found here.

**Lecture #44 ****(officially renamed "Hogg and Craig Lectures" when Professor Hogg passed away in 2014) - 2015**

Richard L. Dykstra, University of Iowa, "Fifty Years of Statistical Memories" and "Von Neumann's Alternating Projections and Dykstra's Algorithm"*We also celebrated our department's "Semi-Centennial Symposium" this year*

**Lecture #43 - 2014**

Jianqing Fan, Princeton University. His lectures were "Statistical Challenges in Analysis of Big Data" and "Homogeneity Pursuit"

**Lecture #42 - 2013**

Paul Embrechts, ETH Zurich, “Thinking about Extremes” and “Model Uncertainty and Risk Aggregation”

**Lecture #41 - 2012**

Rob Tibshirani, Stanford University, “Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data” and “The lasso: some novel algorithms and applications”

**Lecture #40 - 2011**

Alan Gelfand, Duke University, "Space is the Place: Why spatial thinking matters for environmental problems" and "Point pattern modeling for degraded presence-only data over large regions"

**Lecture #39 - 2010**

Terry Speed, University of California at Berkley, "Removing Unwanted Variation From Microarray Data and Analysis of ChIP-Seq Data"

**Lecture #38 - 2009**

George Casella, University of Florida, "Estimation in Dirichlet Random Effects Models" and "From R. A. Fisher to Microarrays: Why 70-Year-Old Theory is Relevant Today"

**Lecture #37 - 2007**

Nancy Reid, University of Toronto, "Weighting the Likelihood Function" and "Putting Asymptotics to Work"

**Lecture #36 - 2006**

Alan Agresti, University of Florida, "Reducing Conservatism of Exact Small-Sample Inference for Discrete Data" and "A Twentieth Century Tour of Categorical Data Analysis"

**Lecture #35 - 2005**

Jay Kadane, Carnegie Mellon University, "Driving While Black: Differential Enforcement of the Traffic Laws on the New Jersey Turnpike" and "Is Ignorance Bliss?"

**Lecture #34 - 2004**

Jim Berger, Duke University, "Objective Bayesian Analysis: Its Uses in Practice and Its Role in the Unification of Statistics" and "Validation of Computer Models"

**Lecture #33 - 2003**

Elizabeth Thompson, University of Washington, "Linkage Detection for Complex Traits" and "Monte Carlo Estimation of Likelihood Functions: The Example of Multipoint Linkage LOD Scores"

**Lecture #32 - 2001**

Luke Tierney, University of Minnesota-Twin Cities, "Some Adaptive Monte Carlo Methods for Bayesian Inference" and "Some Issues in the Design of R"

**Lecture #31 - 2000**

Hans Gerber, University of Lausanne (Switzerland), "Trees R Us: From Kronecker and Esscher to Black and Scholes" and "Pricing Perpetual Options for Jump Processes: From Risk Theory to Finance"

**Lecture #30 - 1999**

Howell Tong, London School of Economics and University of Hong Kong, "Chaos in Statistics" and "Some Recent Non-Parametric Tools in Nonlinear Time Series"

**Lecture #29 - 1998**

Ulf Grenander, Brown University, "Computational Anatomy" and "A Bayesian Approach to Vision"

**Lecture #28 - 1997**

John A. Hartigan, Yale University, "The Effect of Proposition 48 on Graduation Rates of American Athletes" and "The Maximum Likelihood Prior"

**Lecture #27 - 1996**

Trevor Hastie, Stanford University, "Flexible Discriminant and Mixture Models" and "Metrics and Models for Handwritten Digit Recognition"

**Lecture #26 - 1995**

F.T. (Tim) Wright, University of Missouri-Columbia, "Harnessing Chance" and "Pseudo Likelihood Inferences for Ordered Survival Curves Under the Assumption of Proportional Hazards"

**Lecture #25 - 1994**

Peter McCullagh, University of Chicago, "The Role of Models in Statistics" and "Some Remarks on Over-Dispersion"

**Lecture #24 - 1993**

Herman Chernoff, Harvard University, "An Application of a Result of Elfving on the Optimal Design of Regression Experiments" and "The Distribution of the Likelihood-Ratio for Mixtures of Distributions with Application to Genetics"

**Lecture #23 - 1992**

Herbert Robbins, Columbia University, "Big N, Little n: Minimizing the Ethical Cost of a Clinical Trial" and "Estimation Under Biased Allocation"

**Lecture #22 - 1991**

T.W. Anderson, Stanford University, "R.A. Fisher and Multivariate Analysis" and "Goodness-of-fit Tests for Spectral Distributions"

**Lecture #21 - 1990**

Thomas P. Hettmansperger, Pennsylvania State University, "Simple Sign Based Inference in the Location Model" and "Rank Based Inference in the Linear Model".

**Lecture #20 - 1989**

Ron Pyke, University of Washington, "The Bell-Shaped Curve: A Central Role for Probability in Statistics" and "Set-Indexed Empirical, Quantile and Rank Processes".

**Lecture #19 - 1988**

Tom Ferguson, University of California-Berkeley, "Who Solved the Secretary Problem?" and "Some Time-Invariant Stopping Rule Problems".

**Lecture #18 - 1987**

Carl Morris, University of Texas, "Parametric Empirical Bayes: An Overview" and "Bayesian Empirical Bayes Interval Estimation: A Review of Recent Progress".

**Lecture #17 - 1986**

Steve Stigler, University of Wisconsin, "John Craig and the Probability of History" and "The History of Statistics in the Social Science: Recovering from the Central Limit Disaster"

**Lecture #16 - 1985**

George E.P. Box, University of Wisconsin, "Analyzing Fractional Designs" and "Thoughts on Some Ideas of Genichi Taguchi"

**Lecture #15 - 1984**

Wayne Fuller, Iowa State University, "Measurement Error in Regression" and "Nonlinear Measurement Error Models"

**Lecture #14 - 1983**

J. Stuart Hunter, Princeton University, "Theory Sigma: Quality Through Statistical Methods" and "Fractional Factorials: Sequential and Prior Analysis"

**Lecture #13 - 1982**

Colin L. Mallows, Bell Telephone Laboratories, "Robust Methods -- Applications and Basic Concepts" and "Robust Methods: Theory"

**Lecture #12 - 1981**

David J. Bartholomew, London School of Economics and Political Science" and "Latent Variable Models in Statistics"

**Lecture #11 - 1980**

James C. Hickman, University of Wisconsin, "The Great Rates of Retirement Planning: Wages, Interest and Population" and "Bayesian Bivariate Graduation and Forecasting"

**Lecture #10 (officially renamed "Allen T. Craig Lecture Series" when Professor Craig passed away in 1978) - 1979**

Robert V. Hogg, University of Iowa, "On Statistics at Iowa: Before 1950" and "On Statistics at Iowa: After 1950"

**Lecture #9 - 1978**

J.L. Doob, University of Illinois, "A Discrete Boundary Value Problem" and "A General First Boundary Value Problem for Laplace's Equation"

**Lecture #8 - 1977**

Frank Proschan, Florida State University, "A Class of Multivariate Functions in Ranking Problems" and "A Case History: Explaining an Observed Decreasing Failure Rate"

**Lecture #7 - 1976**

Brad Efron, Stanford University, "How Many Words Did Shakespeare Know?" and "Regression and ANOVA with 0-1 Data"

**Lecture #6 - 1975**

Dennis V. Lindley, University College, London, "Getting Married and Related Problems" and "Analysis of Variance"

**Lecture #5 - 1974**

Jack Kiefer, Cornell University, "Foundations of Statistics: Are There Any?" and "How to Find an Optimum Design"

**Lecture #4 - 1973**

H.D. Brunk, Oregon State University, "Bayesian Inference: Some Introductory Illustrations" and "Some Bayesian Approaches to Nonparametric Estimation"

**Lecture #3 - 1972**

William Kruskal, University of Chicago, "Federal Statistics: People and Problems" and "Statistics: Public Policy and Private Understanding"

**Lecture #2 - 1971**

Frederick Mosteller, Harvard University, "Statistics in Society"

**Lecture #1 - 1970**

Allen T. Craig, University of Iowa, "Retirement Talk"