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The Department of Mathematical Sciences has a small active group of
statisticians. Their interests are in the theory and applications of statistics.
Specific research interests include nonparametric correlation and regression,
logistic regression and applications, applications of statistics in ecology
and natural resource economics, spatial statistics, and discriminant analysis.
A general interest statistics seminar meets weekly. Recent topics include
bootstrapping, generalized linear models, general statistical techniques
using a nonparametric correlation coefficient, S-Plus, and spatial statistical
methods. Each year the department offers courses at the
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junior, senior and graduate levels for majors as well as many services courses for non-majors at
all levels. These courses cover mathematical and applied statistics and
statistical inference at beginning and advanced levels, computer data analysis,
nonparametric statistics, linear models, sampling methods, experimental
design, time series and other special topics. Use of computers is an integral
component in nearly all statistics courses. Software available includes
Data Desk, S-Plus, SPSS, Mathematica and Maple. The department has 2 PC
labs, and a departmental network with Unix workstations.
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Statistics Faculty:
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Solomon Harrar, Ph.D., Bowling Green State University, 2004.
Rudy Gideon,
(Emeritus), Ph.D., University of Wisconsin, 1970.
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Currently preparing 1/2 day workshop for the August ASA meeting on the
general use of correlation coefficients in statistical estimation.
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A Rank Correlation Coefficient Resistant to Outliers, JASA, Vol.
82 (1987), no. 398, pp. 656-666.
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The Nonparametric Correlation Coefficient as a Comprehensive Robust Statistical
Tool, a talk in an invited speaker session, Western Regional Meeting
of IMS, Biometric Society, June 1994.
Jonathan
Graham, Ph.D., North Carolina State University, 1995
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Markov Chain Monte Carlo Methods for Modeling the Spatial Pattern of Disease
Spread in Bell Pepper, Proceedings of the 1996 Kansas State University
Conference on Applied Statistics in Agriculture, pp. 91-108, April
1997.
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Autologistic Model of Spatial Pattern of Phytophthova Epidemic in Bell
Pepper: Effects of Soil Variables on Disease Presence, with M.L. Gumpertz
and J.B. Ristaino, Journal of Agriculture, Biology, and Environmental
Statistics, Vol. 2, No. 2, pp. 131-156, 1997.
Don Loftsgaarden
(Emeritus), Ph.D., Montana State University, 1964
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Statistical Abstract of Undergraduate Programs in the Mathematical Sciences
in the United States, Fall 1995 CBMS Survey, with Donald C. Rung
and Anne E. Watkins, MAA Reports No. 2, The Mathematical Association
of America, 1997, 189 pages. Funded by the National Science Foundation.
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Statistical Abstract of Undergraduate Programs in the Mathematical Sciences
and Computer Science in the United States, 1990-1991 CBMS Survey, with
Donald Albers, Donald Rung and Anne Watkins, MAA Notes No. 23, The Mathematical
Association of America, 1992, 173 pages. Funded by the National Science
Foundation.
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Constructing and Testing Logistic Regression Models for Binary Data: Applications
to the National Fire Danger Rating System, with Patricia Andrews,
May 1992, 36 pages. U.S. Forest Service, Intermountain Research Station,
General Technical Report INT-286.
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David Patterson,
Ph.D., University of Iowa, 1984
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Constrained Discriminant Analysis via 0/1 Mixed Integer Programming, with
R. Gallagher and E. Lee, Annals of Operations Research, 74, 65-88
(1997).
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Power of Sign Surveys to Monitor Population Trend, with K. Kendall,
L. Metzgar and B. Steele, Ecological Applications, 2(4), 422-430
(1992).
Brian Steele, Ph.D., The University
of Montana, 1995
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Ideal Bootstrap Estimation of Expected Prediction Error for k-Nearest
Neighbor Classifiers: Applications for Classification and Error Assessment,
with D. Patterson, accepted by Statistics and Computing.
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Estimation and Mapping of Misclassification Probabilities for Thematic
Land Cover Maps, with J.C. Winne and R.L. Redmond, Remote Sensing and
Environment, 66, 192-202, (1998).
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A Modified EM Algorithm for Estimation in Generalized Mixed Models, Biometrics,
52, 1295-1310, (1996).
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