Courses - Fall 2024
STAT100
Prerequisite: MATH110, MATH112, MATH113, or MATH115; or permission of CMNS-Mathematics department; or must have math eligibility of STAT100 or higher and math eligibility is based on the Math Placement Exam or the successful completion of Math 003 with appropriate eligibility.
Restriction: Must not have completed MATH111; or must not have completed any STAT course with a prerequisite of MATH141.
Cross-listed with: DATA100.
Credit only granted for: DATA100 or STAT100.
Simplest tests of statistical hypotheses; applications to before-and-after and matched pair studies. Events, probability, combinations, independence. Binomial probabilities, confidence limits. Random variables, expected values, median, variance. Tests based on ranks. Law of large numbers, normal approximation. Estimates of mean and variance.
STAT110
Applications of R for Data Science
Credits:
1
Grad Meth:
Reg, P-F, Aud
Prerequisite: DATA100, STAT100, or MATH135; or any 400-level STAT course.
Cross-listed with: DATA110.
Credit only granted for: STAT110 or DATA110.
Intended to prepare students for subsequent courses requiring computation with R, providing powerful and easy to use tools for statistical data analysis. Covers basics of R and R Studio including file handling, data simulation, graphical displays, vector and function operations, probability distributions, and inferential techniques for data analysis.
STAT386
Experiential Learning
Credits:
3 - 6
Grad Meth:
Reg, P-F
Prerequisite: Must have learning proposal approved by the CMNS-Mathematics Department.
STAT400
Applied Probability and Statistics I
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (MATH131, MATH141); or students who have taken courses with comparable content may contact the department.
Cross-listed with: DATA400.
Credit only granted for: DATA400, ENEE324, or STAT400.
Additional information: Not acceptable toward graduate degrees in MATH/STAT/AMSC.
Random variables, standard distributions, moments, law of large numbers and central limit theorem. Sampling methods, estimation of parameters, testing of hypotheses.
STAT401
Applied Probability and Statistics II
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (STAT400, STAT410).
Additional information: Not acceptable toward graduate degrees in MATH/STAT/AMSC.
Point estimation - unbiased and consistent estimators. Interval estimation. Minimum variance and maximum likelihood estimators. Testing of hypotheses. Regression, correlation and analysis of variance. Sampling distributions. Elements of non-parametric methods.
STAT410
Introduction to Probability Theory
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH461, MATH341); and 1 course with a minimum grade of C- from (MATH340, MATH241).
Cross-listed with: SURV410.
Credit only granted for: STAT410 or SURV410.
Probability and its properties. Random variables and distribution functions in one and several dimensions. Moments. Characteristic functions. Limit theorems.
STAT420
Theory and Methods of Statistics
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (SURV410, STAT410).
Cross-listed with: SURV420.
Credit only granted for: STAT420 or SURV420.
Point estimation, sufficiency, completeness, Cramer-Rao inequality, maximum likelihood. Confidence intervals for parameters of normal distribution. Hypothesis testing, most powerful tests, likelihood ratio tests. Chi-square tests, analysis of variance, regression, correlation. Nonparametric methods.
STAT426
Introduction to Data Science and Machine Learning
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: Minimum grade of C- in MATH241 or MATH340; and minimum grade of C- in MATH240, MATH461 or MATH341; and minimum grade of C- in STAT400 or STAT410; students who have taken courses with content comparable to STAT400/410 may request permission of the instructor.
Credit only granted for: STAT426 or CMSC320.
An introductory course to the recent developments in the fields of data science and machine learning. Emphasis will be given to mathematical and statistical understanding of commonly used methods and processes.
STAT430
Introduction to Statistical Computing with SAS
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (STAT400, STAT410); and must have completed or be concurrently enrolled in STAT401 or STAT420; students who do not meet the STAT401 or STAT420 requirement but who have taken a statistics course may contact the math department to confirm eligibility.
Descriptive and inferential statistics. SAS software: numerical and graphical data summaries; merging, sorting and splitting data sets. Least squares, regression, graphics and informal diagnostics, interpreting results. Categorical data, lifetime data, time series. Applications to engineering, life science, business and social science.
STAT440
Sampling Theory
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (STAT401, STAT420).
Credit only granted for: STAT440 or SURV440.
Simple random sampling. Sampling for proportions. Estimation of sample size. Sampling with varying probabilities. Sampling: stratified, systematic, cluster, double, sequential, incomplete.
STAT464
Introduction to Biostatistics
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: Must have completed one semester of calculus.
Restriction: Junior standing or higher.
Credit only granted for: BIOE372 or STAT464.
Additional information: Not acceptable toward degrees in MATH/STAT.
Probabilistic models. Sampling. Some applications of probability in genetics. Experimental designs. Estimation of effects of treatments. Comparative experiments. Fisher-Irwin test. Wilcoxon tests for paired comparisons.
STAT470
Actuarial Mathematics
Credits:
3
Grad Meth:
Reg, P-F, Aud
Prerequisite: 1 course with a minimum grade of C- from (MATH240, MATH461, MATH341); and 1 course with a minimum grade of C- from (MATH340, MATH241).
Recommended: STAT400.
Major mathematical ideas involved in calculation of life insurance premiums, including compound interest and present valuation of future income streams; probability distribution and expected values derived from life tables; the interpolation of probability distributions from values estimated at one-year multiples; the 'Law of Large Numbers' describing the regular probabilistic behavior of large populations of independent individuals; and the detailed calculation of expected present values arising in insurance problems.
STAT498A
Selected Topics in Statistics
Credits:
1 - 6
Grad Meth:
Reg, P-F, Aud
STAT600
Probability Theory I
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: STAT410.
Probability space; distribution functions and densities; Poissson limit theoreom; de Moivre-Laplace theorem; measure-theoretic definition of expectation; classification of measures on R; convergence of random variables; Radon-Nikodym theorem;LP spaces; conditional probabilities; independence of events, sigma-algebras and random variables; Bayes' theo rem; pi-systems and Dynkin systems; discrete Markov chains; random walks; gambler's ruin problem; Markov chains on a general phase space; Borel-cantelli lemmas; Kolmogorov inequality; three series theorem; laws of large numbers.
STAT689
Research Interactions in Statistics
Credits:
1 - 3
Grad Meth:
Reg, Aud
STAT700
Mathematical Statistics I
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: STAT410; or students who have taken courses with comparable content may contact the department.
Sampling distributions including noncentral chi-squared, t, F. Exponential families, completeness. Sufficiency, factorization, likelihood ratio. Decision theory, Bayesian methods, minimax principle. Point estimation. Lehmann-Scheffe and Cramer-Rao theorems. Set estimation.
Offered fall only.
STAT705
Computational Statistics
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: STAT700 or STAT420.
Recommended: Have some programming experience (any language).
Credit only granted for: STAT705 or STAT798C.
Formerly: STAT798C.
Modern methods of computational statistics and their application to both practical problems and research. S-Plus and SAS programming with emphasis on S-Plus. S-Plus objects and functions, and SAS procedures. Topics include data management and graphics, Monte Carlo and simulation, bootstrapping, numerical optimization in statistics, linear and generalized linear models, nonparametric regression, time series analysis.
STAT740
Linear Statistical Models I
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: STAT700 or STAT420.
Least squares, general linear models, estimability and Gauss-Markov theorem. Simple and multiple linear regression, analysis of residuals and diagnostics, polynomial models, variable selection. Qualitative predictors, one and two way analysis of variance, multiple comparisons, analysis of covariance. Nonlinear least squares. High-level statistical computer software will be used for data analysis throughout the course.
STAT799
Master's Thesis Research
Credits:
1 - 6
Grad Meth:
S-F
STAT808A
Selected Topics in Probability
Credits:
1 - 3
Grad Meth:
Reg, Aud
STAT818A
Selected Topics in Statistics
Credits:
1 - 3
Grad Meth:
Reg, Aud
STAT818J
Selected Topics in Statistics; Large Deviations
Credits:
1 - 3
Grad Meth:
Reg, Aud
STAT818N
Selected Topics in Statistics; Statistical Foundations of Deep Neural Network Models
Credits:
1 - 3
Grad Meth:
Reg, Aud
STAT898
Pre-Candidacy Research
Credits:
1 - 8
Grad Meth:
Reg
STAT899
Doctoral Dissertation Research
Credits:
6
Grad Meth:
S-F
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