

Twin Cities Courses

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STATISTICS (STAT)
College of Liberal Arts
Statistics, School ofADM


STAT
1001
 Introduction to the Ideas of Statistics
(MATH)
(4.0 cr; PrereqMathematics requirement for admission to University; fall, spring, summer, every year) Graphical/numerical presentations of data. Judging the usefulness/reliability of results/inferences from surveys and other studies to interesting populations. Coping with randomness/variation in an uncertain world.
STAT
1905
 Freshman Seminar
(3.0 cr [max 6.0 cr]; AF or Aud, fall, offered periodically) Topics specified in Class Schedule.
STAT
3011
 Introduction to Statistical Analysis
(MATH)
(4.0 cr; =[STAT 5021, ANSC 3011, ESPM 3012]; fall, spring, summer, every year) Standard statistical reasoning. Simple statistical methods. Social/physical sciences. Mathematical reasoning behind facts in daily news. Basic computing environment.
STAT
3021
 Introduction to Probability and Statistics
(3.0 cr; PrereqMath 1272; fall, spring, summer, every year) Elementary probability, probability distributions. Sampling, elements of statistical inference. Regression.
STAT
3022
 Data Analysis
(4.0 cr; Prereq3011 or 3021 or SOC 3811; fall, spring, every year) Practical survey of applied statistical inference/computing covering widely used statistical tools. Multiple regression, variance analysis, experiment design, nonparametric methods, model checking/selection, variable transformation, categorical data analysis, logistic regression.
STAT
4101
 Theory of Statistics I
(4.0 cr; =[STAT 5101]; PrereqMath 1272; fall, every year) Random variables/distributions. Generating functions. Standard distribution families. Data summaries. Sampling distributions. Likelihood/sufficiency.
STAT
4102
 Theory of Statistics II
(4.0 cr; =[STAT 5102]; Prereq4101; spring, every year) Estimation. Significance tests. Distribution free methods. Power. Application to regression and to analysis of variance/count data.
STAT
4893W
 Senior Project
(WI)
(3.0 cr; PrereqStat major (BA or BS), Sr, 5302; AF only, fall, spring, every year) Statistical data in business, public sector, academic settings. Student analysis of data. Write reports. Create informative/userfriendly visuals. Prepare summaries of statistical research, design research. Write academic paper.
STAT
4932
 Topics in Statistics
(3.0 cr; Prereq#) Topics vary according to student needs and available staff.
STAT
5021
 Statistical Analysis
(4.0 cr; =[STAT 3011, ANSC 3011, ESPM 3012]; Prereq=: 3011; College algebra or #; Stat course recommended; fall, spring, every year) Intensive introduction to statistical methods for graduate students needing statistics as a research technique.
STAT
5031
 Statistical Methods for Quality Improvement
(4.0 cr; Prereq[3021 or 3022 or 4102 or 5021 or 5102 or 8102], Math 1272; spring, offered periodically) Random variability/sampling. Controlling statistical process. Shewhart/accumulative charting. Analyzing plant data, trend surface, and variance/design of experiments.
STAT
5041
 Bayesian Decision Making
(3.0 cr; Prereq4101 or 5021 or 5101 or #) Axioms for subjective probability/utility. Optimal statistical decision making. Sequential decisions/decision trees. Backward induction. Bayesian data analysis.
STAT
5101
 Theory of Statistics I
(4.0 cr; =[STAT 4101]; PrereqMATH 2263 or MATH 2374; fall, every year) Logical development of probability, basic issues in statistics. Probability spaces. Random variables, their distributions and expected values. Law of large numbers, central limit theorem, generating functions, multivariate normal distribution.
STAT
5102
 Theory of Statistics II
(4.0 cr; =[STAT 4102]; Prereq5101 or Math 5651; spring, every year) Sampling, sufficiency, estimation, test of hypotheses, size/power. Categorical data. Contingency tables. Linear models. Decision theory.
STAT
5201
 Sampling Methodology in Finite Populations
(3.0 cr; Prereq3022 or 4102 or 5021 or 5102 or #; spring, every year) Simple random, systematic, stratified, unequal probability sampling. Ratio, model based estimation. Single stage, multistage, adaptive cluster sampling. Spatial sampling.
STAT
5302
 Applied Regression Analysis
(4.0 cr; Prereq3022 or 4102 or 5021 or 5102 or #; fall, spring, summer, every year) Simple, multiple, and polynomial regression. Estimation, testing,
prediction. Use of graphics in regression. Stepwise and other
numerical methods. Weighted least squares, nonlinear models,
response surfaces. Experimental research/applications.
STAT
5303
 Designing Experiments
(4.0 cr; Prereq3022 or 4102 or 5021 or 5102 or #; fall, spring, summer, every year) Analysis of variance. Multiple comparisons. Variancestabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design.
STAT
5401
 Applied Multivariate Methods
(3.0 cr; Prereq5302 or 8102 or #; fall, offered periodically) Bivariate and multivariate distributions. Multivariate normal distributions. Analysis of multivariate linear models. Repeated measures, growth curve and profile analysis. Canonical correlation analysis. Principle components and factor analysis. Discrimination, classification, and clustering.
STAT
5421
 Analysis of Categorical Data
(3.0 cr; Prereq5302 or #; fall, spring, every year) Varieties of categorical data, crossclassifications, contingency tables. Tests for independence. Combining 2x2 tables. Multidimensional tables/loglinear models. Maximumlikelihood estimation. Tests for goodness of fit. Logistic regression. Generalized linear/multinomialresponse models.
STAT
5511
 Time Series Analysis
(3.0 cr; PrereqTheoretical understanding; fall, every year) Characteristics of time series. Stationarity. Secondorder descriptions, timedomain representation, ARIMA/GARCH models. Frequency domain representation. Univariate/multivariate time series analysis. Periodograms, non parametric spectral estimation. Statespace models.
STAT
5601
 Nonparametric Methods
(3.0 cr; Prereq3022 or 4102 or 5021 or 5102 or #; fall, spring, every year) Order statistics. Classical rankbased procedures (e.g., Wilcoxon, KruskalWallis). Goodness of fit. Topics may include smoothing, bootstrap, and generalized linear models.
STAT
5701
 Statistical Computing
(3.0 cr; Prereq4102 or 5102 or 8102 or #; AF or Aud, fall, every year) Statistical programming, function writing, graphics using highlevel statistical computing languages. Data management, parallel computing, version control, simulation studies, power calculations. Using optimization to fit statistical models. Monte Carlo methods, reproducible research.
STAT
5931
 Topics in Statistics
(3.0 cr; fall, offered periodically) Topics vary according to student needs and available staff.
STAT
5932
 Topics in Statistics
(3.0 cr; fall, spring, offered periodically) Topics vary according to students' needs and available staff.
STAT
5993
 Tutorial
(1.0  6.0 cr [max 12.0 cr]; Prereq#; fall, spring, summer, every year) Directed study in areas not covered by regular offerings.
STAT
8051
 Advanced Regression Techniques: linear, nonlinear and nonparametric methods
(3.0 cr; PrereqStatistics grad or #; AF or Aud, fall, every year) Linear/generalized linear models, modern regression methods including nonparametric regression, generalized additive models, splines/basis function methods, regularization, bootstrap/other resamplingbased inference.
STAT
8052
 Applied Statistical Methods 2: Design of Experiments and Mixed Effects Modeling
(3.0 cr; Prereq8051 or #; AF or Aud, spring, every year) Design experiments/analyze data with fixed effects, random/mixed effects models. ANOVA for factorial designs. Contrasts, multiple comparisons, power/sample size, confounding, fractional factorials. Computergenerated designs. Response surfaces. Multilevel models. Generalized estimating equations (GEE) for longitudinal data with nonnormal errors.
STAT
8053
 Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression
(3.0 cr; Prereq8052, 8102; AF or Aud, fall, every year) Standard multivariate analysis. Multivariate linear
model, classification, clustering, principal components, factor analysis, canonical correlation. Topics in advanced regression.
STAT
8054
 Statistical Methods 4: Advanced Statistical Computing
(3.0 cr; Prereq8053 or #; AF or Aud, spring, every year) Optimization, numerical integration, Markov chain Monte Carlo, related topics.
STAT
8055
 Applied Project
(2.0 cr; Prereq[8054, 8801] or #; SN only, fall, every year) Collaborative applied statistical practice with a member of University community, including consulting, problem solving, presentation/documentation of results.
STAT
8101
 Theory of Statistics 1
(3.0 cr; PrereqStatistics grad major or #; fall, every year) Review of linear algebra. Introduction to probability theory. Random variables, their transformations/expectations. Standard distributions, including multivariate Normal distribution. Probability inequalities. Convergence concepts, including laws of large numbers, Central Limit Theorem. delta method. Sampling distributions.
STAT
8102
 Theory of Statistics 2
(3.0 cr; Prereq8101, Statistics graduate major or #; spring, every year) Statistical inference. Sufficiency. Likelihoodbased methods. Point estimation. Confidence intervals. Neyman Pearson hypothesis testing theory. Introduction to theory of linear models.
STAT
8111
 Mathematical Statistics I
(3.0 cr; Prereq[5102 or 8102 or #], [[Math 5615, Math 5616] or real analysis], matrix algebra; fall, every year) Probability theory, basic inequalities, characteristic functions, and exchangeability. Multivariate normal distribution. Exponential family. Decision theory, admissibility, and Bayes rules.
STAT
8112
 Mathematical Statistics II
(3.0 cr; Prereq8111; spring, every year) Statistical inference, estimation, and hypothesis testing.
Convergence and relationship between convergence modes.
Asymptotics of maximum likelihood estimators, distribution
functions, quantiles. Delta method.
STAT
8141
 Probability Assessment
(3.0 cr; Prereq5102; spring, offered periodically) Probability as a language of uncertainty for quantifying and communicating
expert opinion and for use as Bayesian prior distributions. Methods for
elicitation and construction of subjective probabilities. De Finetti
coherence, predictive elicitation, fitting subjectiveprobability models,
computeraided elicitation, and use of experts.
STAT
8171
 Sequential Analysis
(3.0 cr; Prereq8112) Walds's sequential probability ratio test and modifications.
Sequential decision theory. Martingales. Sequential estimation,
design, and hypothesis testing. Recent developments.
STAT
8201
 Topics in Sampling
(3.0 cr; Prereq8102 or #; SN or Aud) Sampling theory; stratified sampling, ratio estimators, cluster sampling, double sampling, superpopulation theory, Bayesian methods, multiple imputation, nonresponse.
STAT
8311
 Linear Models
(4.0 cr; PrereqLinear algebra, 5102 or 8102 or #; fall, every year) General linear model theory from a coordinatefree geometric approach. Distribution theory, ANOVA tables, testing, confidence statements, mixed models, covariance structures, variance components estimation.
STAT
8312
 Linear and Nonlinear Regression
(3.0 cr; Prereq8311) Nonlinear regression: asymptotic theory, BatesWatts curvatures, super leverage, parameter plots, projected residuals, transformbothsides methodology, Wald versus likelihood inference. Topics in linear and generalized linear models as they relate to nonlinearity issues, including diagnostics, semiparametric models, and model assessment.
STAT
8313
 Topics in Experimental Design
(3.0 cr; Prereq8311) Optimal, Bayes, and nonlinear designs; algorithms for computing designs; sample size; recent developments.
STAT
8321
 Regression Graphics
(3.0 cr; Prereq8311) Foundations: dimensionreduction subspaces, LiDuan Lemma, structural dimension. Inferring about central dimensionreduction subspaces by using 3D plots, graphical regression, inverse regression graphics, neteffect plots, principal Hessian directions, sliced inverse regression and predictor transformations. Graphics for model assessment.
STAT
8333
 FTE: Master's
(1.0 cr; PrereqMaster's student, adviser and DGS consent; No Grade, fall, spring, summer, every year) (No description)
STAT
8401
 Topics in Multivariate Methods
(3.0 cr; Prereq8311; fall, every year) Bivariate and multivariate distributions. Multivariate normal distributions. Hotellings's Tsquared, MANOVA, MANCOVA, and regression
with multivariate dependent variable. Repeated measures, growth curve, and
profile analysis. Canonical correlation analysis. Principle components and
factor analysis. Discrimination, classification, clustering.
STAT
8411
 Multivariate Analysis
(3.0 cr; Prereq8152; fall, spring, offered periodically) Multivariate normal distribution. Inference on the mean, covariance, and
correlation and regression coefficients; related sampling distributions such as Hotelling's Tsquared and Wishart distributions. Multivariate analysis of variance. Principal components and canonical correlation. Discriminant analysis.
STAT
8421
 Theory of Categorical Data Analysis
(3.0 cr; Prereq8062 or #) Categorical data, multidimensional crossclassified arrays, mixed categorical and continuous data. Loglinear, logit, and multinomial response models. Ordinal responses. Current research topics.
STAT
8444
 FTE: Doctoral
(1.0 cr; PrereqDoctoral student, adviser and DGS consent; No Grade, fall, spring, summer, every year) (No description)
STAT
8501
 Introduction to Stochastic Processes with Applications
(3.0 cr; Prereq5101 or 8101) Markov chains in discrete and continuous time, renewal processes,
Poisson process, Brownian motion, and other stochastic models
encountered in applications.
STAT
8511
 Time Series Analysis
(3.0 cr; Prereq5102 or 8111 or #) Characteristics of time series. Stationarity. Secondorder descriptions. Timedomain representation, ARIMA/GARCH models. Frequency domain representation, univariate/multivariate analysis. Periodograms, nonparametric spectral estimation, state space models.
STAT
8666
 Doct PreThesis Cr
(1.0  6.0 cr [max 12.0 cr]; PrereqDoctoral student who has not passed prelim oral; no required consent for 1st/2nd registrations, up to 12 combined cr; % for 3rd/4th registrations, up to 24 combined cr; doctoral student admitted before summer 2007 may register up to four times, up to 60 combined cr; No Grade, fall, spring, summer, every year) TBD
STAT
8701
 Computational Statistical Methods
(3.0 cr; Prereq8311, programming exper; spring, every year) Random variate generation, variance reduction techniques. Robust
location estimation and regression, smoothing additive models,
regression trees. Programming projects; basic programming ability
and familiarity with standard highlevel language (preferably
FORTRAN or C) are essential.
STAT
8711
 Statistical Computing
(3.0 cr; Prereq8701 or #) Basic numerical analysis for statisticians. Numerical methods for linear
algebra, eigenanalysis, integration, and optimization and their statistical applications.
STAT
8721
 Programming Paradigms and Dynamic Graphics in Statistics
(3.0 cr; Prereq8062, 8102) Alternative programming paradigms to traditional procedural programming, including objectoriented programming and functional programming. Applications to development of dynamic statistical graphs and representation and use of functional data, such as mean function in nonlinear regression log likelihoods and prior densities in Bayesian analysis.
STAT
8777
 Thesis Credits: Master's
(1.0  18.0 cr [max 50.0 cr]; PrereqMax 18 cr per semester or summer; 10 cr total required [Plan A only]; No Grade, fall, spring, every year) (No description)
STAT
8801
 Statistical Consulting
(3.0 cr; PrereqSTAT 8051 and STAT Grad Student or Instructor Consent; SN or Aud, spring, every year) Principles of effective consulting/problemsolving, meeting skills, reporting. Aspects of professional practice/behavior, ethics, continuing education.
STAT
8811
 Statistical Consulting Practicum
(3.0 cr [max 12.0 cr]; PrereqStatistics grad student or #; SN or Aud, fall, spring, every year) Providing (under faculty supervision) statistical support to clients, primarily University researchers. Exercises in problem solving, ethics, listening/communication skills.
STAT
8821
 Curricular Practical Training
(1.0 cr [max 3.0 cr]; PrereqStatistics grad student, %; SN only, fall, spring, summer, every year) Industrial work assignment using advanced statistical techniques. Grade based on final report and presentation covering work assignment.
STAT
8888
 Thesis Credit: Doctoral
(1.0  24.0 cr [max 100.0 cr]; PrereqMax 18 cr per semester or summer; 24 cr required; No Grade, fall, spring, every year) (No description)
STAT
8900
 Student Seminar
(1.0 cr [max 2.0 cr]; PrereqStatistics graduate student; SN or Aud, fall, spring, every year) Preparation or presentation of seminar on statistical topics.
STAT
8913
 Literature Seminar
(1.0 cr [max 4.0 cr]; PrereqStatistics grad major or #; SN only, fall, spring, every year) Students will read, present, discuss, and critique current literature/research.
STAT
8931
 Advanced Topics in Statistics
(3.0 cr [max 12.0 cr]; fall, spring, offered periodically) Topics vary according to student needs/available staff.
STAT
8932
 Advanced Topics in Statistics
(3.0 cr [max 12.0 cr]; fall, spring, offered periodically) Topics vary according to student needs/available staff.
STAT
8933
 Advanced Topics in Statistics
(3.0 cr [max 12.0 cr]; fall, spring, every year) Topics vary according to student needs and available staff.
STAT
8992
 Directed Readings and Research
(1.0  6.0 cr [max 12.0 cr]; Prereq#; fall, spring, summer, every year) Directed study in areas not covered by regular offerings.






