To complete this research-methods topic, a student is required to take either 2 or 3 of the following 9 courses. The total number of courses (2 or 3) is determined by the student's Major Area. This research-methods topic has as a pre-requisite the Applied Statistics research-methods topic.

ECON 672 Topics in Econometrics (Unless used to fulfill the Applied Statistics research-methods topic) Topics to include panel data techniques, unobservable, qualitative, and limited dependent variable models, basic time series analysis, and nonlinear statistical models. Requires students to use instructor-specified statistical package(s).

ECON 673 Time Series Methods This course has as a pre-requisite ECON 672

ECON 674 Cross-sectional Econometrics This course has as a pre-requisite ECON 672

MGMT 677 Research Methods: Applied Multivariate Analysis (Unless used to fulfill the Applied Statistics research-methods topic) Applied multivariate statistical methods such as discriminant analysis and multivariate analysis of variance for research problems found in managerial studies. Requires students to use instructor-specified statistical package(s).

MGMT 679 Nonparametric Methods for Research Distribution-free statistical methods for managerial research. Analysis of location and scale measures, nonparametric comparison procedures, association and contingency table analysis, nonparametric goodness-of-fit procedures, and tests for randomness, nonparametric regression and other measures of association, computer intensive statistical methods

STAT 514 Design of Experiments Fundamentals, completely randomized design; randomized complete blocks; latin square; multiclassification; factorial; nested factorial; incomplete block and fractional replications for 2n ; 3n ; 2m 3n , confounding; 12 lattice designs; general mixed factorials; split plot; analysis of variance in regression models; optimum design. Use of existing statistical programs.

STAT 520 Time Series and Applications A first course in stationary time series with applications in engineering, economics, and physical sciences. Stationarity, autocovariance function and spectrum; integral representation of a stationary time series and interpretation; linear filtering, transfer functions; estimation of spectrum; multivariate time series. Use of computer programs for covariance and spectral estimation.

STAT 524 Applied Multivariate Analysis (Unless used to fulfill the Applied Statistics research-methods topic) Extension of univariate tests in normal populations to the multivariate case, equality of covariance matrices, multivariate analysis of variance, discriminant analysis and misclassification errors, canonical correlation, principal components, factor analysis. Strong emphasis will be placed on use of existing computer programs.

STAT 526 Advanced Statistical Methodology Computationally intensive methods in statistics including bootstrapping, Monte Carlo simulation, nonparametric density estimation, nonparametric regression and methods appropriate for high-dimensional data. Extensive use is made of statistical software.

STAT 529 Bayesian Statistics and Applied Decision Theory Bayesian and decision theoretic formulation of problems; construction of utility functions and quantifications of prior information; methods of Bayesian decision and inference, with applications; empirical Bayes; combination of evidence; Bayesian design and sequential analysis; comparisons of statistical paradigms.

STAT 657 Mathematical Statistics I Sequential analysis. Sequential probability ratio test. Approximations. Open-ended tests. Sequential Bayes rules. Robustness. Complete class theorems. Monotone likelihood ratio families. Essentially complete classes. Most powerful tests in restricted classes. Unbiasedness. Similarity. Invariance. Maximal invariants. Most powerful invariant tests.