Course Descriptions

The Course Descriptions catalog describes all undergraduate and graduate courses offered by Michigan State University. The searches below only return course versions Fall 2000 and forward. Please refer to the Archived Course Descriptions for versions prior to Fall 2000.

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Course Descriptions: Search Results

stt 180  Introduction to Data Science

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
(MTH 124 or concurrently) or (MTH 132 or concurrently) or (MTH 152H or concurrently) or (LB 118 or concurrently)
Not open to students with credit in:
STT 301
Description:
Pervasiveness and utility of data in modern society. Obtaining and managing data. Summarizing and visualizing data. Ethical issues in data science. Communication with data. Fundamentals of probability and statistics.
Interdepartmental With:
Computational Mathematics, Science, & Engineering
Administered By:
Statistics and Probability
Effective Dates:
FS19 - Open


STT 191  Selected Topics in Statistics

Semester:
Fall of every year, Spring of every year
Credits:
Variable from 1 to 4
Reenrollment Information:
A student may earn a maximum of 8 credits in all enrollments for this course.
Description:
Topics in statistics and probability selected to complement existing courses.
Effective Dates:
FS18 - Open


STT 200  Statistical Methods

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
(MTH 101 or MTH 102 or MTH 103 or MTH 103B or MTH 116 or MTH 124 or MTH 132 or LB 117 or LB 118) or designated score on Mathematics Placement test
Restrictions:
Open to undergraduate students.
Not open to students with credit in:
STT 201 or STT 421
Description:
Data analysis, probability models, random variables, estimation, tests of hypotheses, confidence intervals, and simple linear regression.
Effective Dates:
US23 - Open


STT 201  Statistical Methods

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 3   Lab Hours: 2
Prerequisite:
(MTH 102 or MTH 103 or MTH 116 or LB 117 or MTH 124 or MTH 132 or LB 118 or MTH 101) or designated score on Mathematics Placement test
Restrictions:
Open to undergraduate students.
Not open to students with credit in:
STT 200 or STT 421
Description:
Probability and statistics with computer applications. Data analysis, probability models, random variables, tests of hypotheses, confidence intervals, simple linear regression. Weekly lab using statistical software.
Effective Dates:
SS23 - Open


stt 224  Introduction to Probability and Statistics for Ecologists

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 2   Lab Hours: 2
Prerequisite:
MTH 103 or MTH 116 or (MTH 124 or concurrently) or (MTH 132 or concurrently) or (MTH 152H or concurrently) or (LB 118 or concurrently)
Recommended Background:
BS 162 or BS 182H or LB 144
Not open to students with credit in:
STT 231
Description:
Probability and statistics with computer applications for the analysis, interpretation and presentation of ecological data. Data analysis, probability models, random variables, estimation, confidence intervals, test of hypotheses, and simple linear regression with applications to ecology.
Semester Alias:
FW 324
Interdepartmental With:
Fisheries and Wildlife
Administered By:
Statistics and Probability
Effective Dates:
FS14 - Open


STT 231  Statistics for Scientists

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
MTH 124 or MTH 132 or MTH 152H or LB 118
Restrictions:
Open to students in the College of Natural Science and open to students in the Lyman Briggs College.
Description:
Calculus-based course in probability and statistics. Probability models, and random variables. Estimation, confidence intervals, tests of hypotheses, and simple linear regression with applications in sciences.
Semester Alias:
STT 331
Effective Dates:
FS19 - Open


STT 250  Statistics and Probability for K-8 Teachers

Semester:
Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
MTH 103
Restrictions:
Open to undergraduate students in the College of Education or approval of department.
Description:
Data collection and analysis. Statistics, probability models. Decision-making in the presence of variability. Computer software relevant for teaching practice.
Effective Dates:
FS14 - Open


STT 290  Topics in Statistics and Probability

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 3
Recommended Background:
MTH 103
Restrictions:
Approval of department.
Description:
Individualized study of selected topics.
Effective Dates:
FS14 - Open


STT 315  Introduction to Probability and Statistics for Business

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
MTH 124 or MTH 132 or MTH 152H or LB 118
Description:
A first course in probability and statistics primarily for business majors. Data analysis, probability models, random variables, confidence intervals, and tests of hypotheses with business applications.
Effective Dates:
FS14 - Open


stt 317  Market Analytics

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 200 or STT 201 or STT 315 or STT 351
Restrictions:
Open to sophomores or juniors or seniors in the Accounting major or in the Business - Admitted major or in the Finance Major or in the Human Resource Management Major or in the Management Major or in the Supply Chain Management Major or in the Marketing Major or in the Applied Engineering Sciences Major.
Description:
Descriptive and predictive market analytics. Applications of analytics to real-world business decisions. Assessment and manipulation of large datasets. Application of statistical techniques to convert data into useable information. Communication of findings in a meaningful way.
Semester Alias:
MSC 317
Interdepartmental With:
Statistics and Probability
Administered By:
Marketing
Effective Dates:
FS19 - Open


STT 351  Probability and Statistics for Engineering

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 234 or MTH 254H or LB 220
Not open to students with credit in:
STT 430
Description:
Probability models and random variables. Estimation, confidence intervals, tests of hypotheses, simple linear regression. Applications to engineering.
Effective Dates:
FS14 - Open


STT 380  Probability and Statistics for Data Science

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
((MTH 234 or concurrently) or (MTH 254H or concurrently) or (LB 220 or concurrently)) and (MTH 314 or concurrently) and STT 180
Description:
Fundamental concepts and methods in probability and statistics from a data science perspective.
Effective Dates:
FS20 - Open


stt 381  Fundamentals of Data Science Methods

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 4
Prerequisite:
(STT 180 and MTH 314 and CMSE 201 and STT 380) or (STT 180 and MTH 314 and CMSE 201 and STT 441 and STT 442)
Description:
Data science methods, including unsupervised learning and supervised learning, feature extraction, dimension reduction, clustering, regression and classification.
Interdepartmental With:
Statistics and Probability
Administered By:
Computational Mathematics, Science, & Engineering
Effective Dates:
FS19 - Open


stt 404  Introduction to Machine Learning

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(CSE 331) and (STT 351 or STT 380 or STT 430 or STT 441) and MTH 314
Recommended Background:
Basic linear algebra
Restrictions:
Open to juniors or seniors in the College of Engineering or in the Computer Science Minor or in the Lyman Briggs Computer Science Coordinate Major or in the Lyman Briggs Computer Science Major or in the Data Science Major.
Description:
Core principles and techniques for machine learning including algorithms, model design, and programming.
Interdepartmental With:
Statistics and Probability, Computational Mathematics, Science, & Engineering
Administered By:
Computer Science and Engineering
Effective Dates:
FS21 - Open


STT 421  Statistics I

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 103 or MTH 116 or MTH 103B or MTH 124 or (MTH 132 or concurrently) or (MTH 133 or concurrently) or (MTH 234 or concurrently) or (MTH 299 or concurrently)
Not open to students with credit in:
STT 200 or STT 201
Description:
Basic probability, random variables, and common distributions. Estimation and tests for one-, two-, and paired sample problems. Introduction to simple linear regression and correlation, one-way ANOVA.
Effective Dates:
US22 - Open


STT 422  Statistics II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 421 or STT 442
Not open to students with credit in:
STT 464
Description:
Goodness of fit and other non-parametric methods. Linear models including multiple regression and ANOVA for simple experimental designs.
Effective Dates:
US22 - Open


STT 430  Introduction to Probability and Statistics

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(MTH 234 or concurrently) or (MTH 254H or concurrently) or (LB 220 or concurrently)
Not open to students with credit in:
STT 351
Description:
Calculus-based probability and statistics with applications. Discrete and continuous random variables and their expectations. Point and interval estimation, tests of hypotheses, and simple linear regression.
Effective Dates:
FS14 - Open


STT 441  Probability and Statistics I: Probability

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 234 or MTH 254H or LB 220 or approval of college
Description:
Probability, conditional probability and independence. Random variables. Discrete, continuous, univariate, and multivariate distributions. Expectation and its properties, moment generating functions. Law of large numbers, central limit theorem.
Effective Dates:
FS17 - Open


STT 442  Probability and Statistics II: Statistics

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 441 and (MTH 309 or MTH 314 or MTH 317H or MTH 415)
Description:
Parameter estimation, sampling distributions, confidence intervals, hypothesis testing, simple and multiple regression, analysis of variance. Time series models, data analysis and forecasting
Effective Dates:
FS17 - Open


stt 455  Actuarial Models I

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 441 and MTH 360
Description:
Stochastic models used in insurance. Survival distributions, life insurance, life annuities, benefit premiums, benefit reserves, and analysis of benefit reserves.
Interdepartmental With:
Mathematics
Administered By:
Statistics and Probability
Effective Dates:
FS14 - Open


stt 456  Actuarial Models II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 455
Description:
Continuation of STT 455. Benefit reserves. Multiple life functions. Multiple decrement models and their applications. Elements of stochastic processes for actuaries including Markov chains and Poisson processes
Interdepartmental With:
Mathematics
Administered By:
Statistics and Probability
Effective Dates:
FS14 - Open


stt 458  Computational Methods in Mathematical Finance and Insurance

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 361 and STT 441
Recommended Background:
MTH 235 or MTH 340 or MTH 347H
Description:
Utilize modern computational methods to price contracts in insurance and mathematical finance. Rational valuation of derivative securities using put-call parity and calculation of European and American options. Introduce hybrid contracts and features, such as equity-indexed annuities.
Interdepartmental With:
Statistics and Probability
Administered By:
Mathematics
Effective Dates:
FS23 - Open


stt 459  Construction and Evaluation of Actuarial Models

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 442
Description:
Severity, frequency, and aggregate models. Construction of empirical models. Parametric statistical methods. Credibility analysis. Simulation methods.
Interdepartmental With:
Mathematics
Administered By:
Statistics and Probability
Effective Dates:
FS14 - Open


STT 461  Computations in Probability and Statistics

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(CMSE 201 or CSE 231) and (MTH 309 or MTH 314 or MTH 317H or MTH 415) and STT 441
Description:
Computer algorithms for evaluation, simulation and visualization. Sampling and prescribed distributions. Robustness and error analysis of procedures used by statistical packages. Graphics for data display, computation of probabilities and percentiles.
Effective Dates:
SS22 - Open


stt 464  Statistics for Biologists

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 103 or MTH 116 or MTH 124 or MTH 132
Recommended Background:
STT 421
Description:
Biological random variables. Estimation of population parameters. Testing hypotheses. Linear correlation and regression. Analyses of counted and measured data to compare several biological groups including contingency tables and analysis of variance.
Interdepartmental With:
Animal Science, Crop and Soil Sciences
Administered By:
Statistics and Probability
Effective Dates:
SS23 - Open


stt 465  Bayesian Statistical Methods

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 442
Description:
Probability, belief, and exchangeability. Objective, subjective, and empirical Bayes approaches. Applications to one-parameter models, linear regression models, and multivariate normal models. Hierarchical modeling. Computational methods.
Interdepartmental With:
Epidemiology
Administered By:
Statistics and Probability
Effective Dates:
FS15 - Open


stt 467  Insurance Operations

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(ACC 230 and FI 321 and MTH 360) and completion of Tier I writing requirement
Recommended Background:
STT 441
Description:
Regulation, marketing and distribution, underwriting, risk control, premium auditing, the claim function, actuarial operations, and reinsurance.
Interdepartmental With:
Mathematics
Administered By:
Statistics and Probability
Effective Dates:
SS19 - Open


stt 468  Predictive Analytics

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(CSE 231) and (MTH 235 or MTH 340) and MTH 360 and STT 442
Description:
Predictive analytics for insurance business and risk management with an emphasis on the use of machine learning tools.
Interdepartmental With:
Statistics and Probability
Administered By:
Mathematics
Effective Dates:
FS19 - Open


STT 481  Capstone in Statistics (W)

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(STT 442 or approval of department) and completion of Tier I writing requirement
Restrictions:
Open to seniors in the Department of Statistics and Probability or approval of department.
Description:
Selected readings and projects illustrating special problems encountered by statisticians in their roles as consultants, educators, researchers and analysts.
Effective Dates:
FS14 - Open


STT 490  Directed Study of Statistical Problems

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 3
Reenrollment Information:
A student may earn a maximum of 9 credits in all enrollments for this course.
Restrictions:
Open to seniors in the Department of Statistics and Probability. Approval of department.
Description:
Individualized study of selected topics.
Effective Dates:
FS14 - Open


stt 492  Selected Topics in Data Science

Semester:
Fall of every year, Spring of every year
Credits:
Variable from 1 to 4
Reenrollment Information:
A student may earn a maximum of 12 credits in all enrollments for this course.
Restrictions:
Approval of department.
Description:
Topics selected to supplement and enrich existing courses in Data Science.
Interdepartmental With:
Computer Science and Engineering, Statistics and Probability
Administered By:
Computational Mathematics, Science, & Engineering
Effective Dates:
FS19 - Open


stt 495  Experiential Learning in Data Science (W)

Semester:
Fall of every year, Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 2   Lab Hours: 4
Prerequisite:
(CSE 232 and CMSE 382) and completion of Tier I writing requirement
Restrictions:
Open to seniors.
Description:
Team-based data science projects working with real-world data in collaboration with client/company sponsors. Practice in software development, data collection, curation, modeling, scientific visualization and presentation of results. Students may be required to sign a non-disclosure agreement (“NDA”) or an assignment of intellectual property rights (“IP Assignment”) to work with some project sponsors.
Interdepartmental With:
Computer Science and Engineering, Statistics and Probability
Administered By:
Computational Mathematics, Science, & Engineering
Effective Dates:
SS23 - Open


stt 800  Quantitative Foundations for Machine Learning

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 132 and MTH 133 or approval of department
Description:
Advanced calculus and linear algebra tools for machine learning algorithms.
Interdepartmental With:
Statistics and Probability
Administered By:
Mathematics
Effective Dates:
US20 - Open


STT 801  Design of Experiments

Semester:
Fall of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 422 or STT 442 or STT 471
Description:
Blocking and randomization. Split-plot, latin square and factorial designs. Fractional factorial designs, aliasing and confounding of effects. Mixture and central composite designs and response surface exploration. Clinical trials.
Effective Dates:
FS08 - Open


STT 802  Statistical Computation

Semester:
Fall of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
(STT 442 and MTH 309) or (mathematical statistics and linear algebra)
Description:
Computational techniques commonly used in Statistics. Matrix decompositions. Least squares and Least Absolute Deviations. Solution of nonlinear equations. Optimization techniques including the EM algorithm and constrained optimization. Numerical integration. Generation of random numbers and stochastic simulation. Implementation in statistical software.
Effective Dates:
SS12 - Open


STT 804  Statistical Consulting and Practice

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Restrictions:
Open to master's students in the College of Natural Science. Approval of department.
Description:
Statistical consulting and the practical aspects of the consulting environment. Ethics. Communication skills. Data management, and statistical methods.
Effective Dates:
FS19 - Open


STT 805  Statistical Modeling for Business Analytics

Semester:
Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442
Restrictions:
Open to master's students in the Business Analytics Major.
Description:
Low dimensional data visualization. Simple linear regression. Regression diagnostics. Analysis of variance. Multiple linear regression. Regression model building. Variable selection. Categorical data. Logistic regression. Proportional odds model. Introduction to time series.
Effective Dates:
US16 - Open


stt 808  Biostatistics I

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
College-level algebra.
Restrictions:
Open to master's students or doctoral students in the Epidemiology major or approval of department.
Description:
Applications of probability and statistics in the applied health sciences. Probability distributions, estimation and tests for one-, two-, and paired samples, linear regression, correlation, and ANOVA. Use of statistical software. Critical appraisal of statistical methods in the biomedical literature.
Semester Alias:
STT 425
Interdepartmental With:
Statistics and Probability
Administered By:
Epidemiology
Effective Dates:
US12 - Open


stt 809  Biostatistics II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
EPI 808
Recommended Background:
MTH 103 or MTH 110 or MTH 116
Restrictions:
Open to master's students or doctoral students in the Epidemiology major or approval of department.
Description:
Analysis of categorical data in epidemiologic studies. Contingency tables and logistic regression.
Semester Alias:
STT 426
Interdepartmental With:
Statistics and Probability
Administered By:
Epidemiology
Effective Dates:
US12 - Open


STT 810  Mathematical Statistics for Data Scientists

Semester:
Fall of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442
Restrictions:
Open to seniors in the Department of Statistics and Probability and not open to graduate students in the Department of Statistics and Probability.
Description:
Random variables. Probability distributions. Transformation of variables. Maximum likelihood estimation. Interval estimation. Hypothesis testing.
Effective Dates:
US22 - Open


STT 811  Applied Statistical Modeling for Data Scientists

Semester:
Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442
Restrictions:
Open to seniors in the Department of Statistics and Probability and not open to graduate students in the Department of Statistics and Probability.
Description:
Data Visualization. Linear regression. Analysis of variance. Logistic regression. Generalized linear models. Variable selection. Categorical data analysis. Models for design of experiments. Models for time series data.
Effective Dates:
US22 - Open


STT 812  Statistical Learning and Data Analysis

Semester:
Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(STT 441 and STT 442) or (STT 810 and STT 811) or (STT 863 and STT 864)
Restrictions:
Open to seniors in the Department of Statistics and Probability and not open to graduate students in the Department of Statistics and Probability.
Description:
Low dimensional data visualization. Linear Regression. Binary Regression. Linear discriminant analysis. Probabilistic classification. Model selection via regularization. LASSO. Non-parametric smoothing. CART. MART. Support vector machine. Neural network. Clustering. Random forest.
Effective Dates:
US22 - Open


stt 814  Advanced Statistics for Biologists

Semester:
Spring of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 3   Lab Hours: 2
Recommended Background:
STT 464
Description:
Concepts of reducing experimental error for biological and agricultural research. Covariance, randomized block designs, latin squares, split plots, repeated-measures designs, regression applications, and response surface designs. Analyses using statistical software.
Interdepartmental With:
Animal Science, Crop and Soil Sciences
Administered By:
Statistics and Probability
Effective Dates:
SS06 - Open


stt 820A  Econometrics IA

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Restrictions:
Open only to doctoral students in the Economics major or the Department of Agricultural Economics or the Business Administration major or approval of department.
Description:
Statistical tools for econometrics. Applications of statistical tools,including probability distributions, estimation, hypothesis testing, and maximum likelihood to econometric problems.
Interdepartmental With:
Statistics and Probability
Administered By:
Economics
Effective Dates:
US02 - Open


STT 825  Sample Surveys

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 422 or STT 442 or STT 862
Description:
Application of statistical sampling theory to survey designs. Simple random, stratified, and systematic samples. Sub-sampling, double sampling. Ratio and regression estimators.
Effective Dates:
FS95 - Open


STT 832  Data Visualization and Programming in R

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Restrictions:
Open to students. Approval of department.
Description:
Development of sports data predictive models. Extraction and management of sport data, graphical and numerical summaries using visualization tools to model practical sports scenarios. Compilation of written reports on test results and performance outputs.
Effective Dates:
FS22 - Open


STT 834  Sports Analytics Capstone

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MTH 501 and STT 502 and MTH 503
Restrictions:
Approval of department.
Description:
Development of quantitative models, based on complex sports-related data sets, to support personnel or revenue-based decision-making from the perspective of a coach, manager, or player agent. Reports, presentations, and code repositories will be delivered.
Effective Dates:
FS22 - Open


STT 843  Multivariate Analysis

Semester:
Spring of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442 or STT 862
Not open to students with credit in:
FW 850
Description:
Multivariate normal distribution, tests of hypotheses on means, multivariate analysis of variance. Discriminant analysis. Principal components. Factor analysis. Analysis of frequency data.
Effective Dates:
US07 - Open


STT 844  Time Series Analysis

Semester:
Spring of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442 or STT 862
Description:
Stationary time series. Autocorrelation and spectra. ARMA and ARIMA processes: estimation and forecasting. Seasonal ARIMA models. Identification and diagnostic techniques. Multivariate time series. Time series software.
Effective Dates:
FS04 - Open


stt 847  Analysis of Survival Data

Semester:
Spring of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 422 or STT 442 or STT 862
Description:
Analysis of lifetime data. Estimation of survival functions for parametric and nonparametric models. Censored data. The Cox proportional hazards model. Accelerated failure time models. Frailty models. Use of statistical software packages.
Interdepartmental With:
Epidemiology
Administered By:
Statistics and Probability
Effective Dates:
FS08 - Open


stt 849  Applied Bayesian Inference using Monte Carlo Methods for Quantitative Biologists

Semester:
Fall of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 2   Lab Hours: 2
Recommended Background:
(STT 814 and IBIO 851) or equivalent courses.
Restrictions:
Not open to undergraduate students.
Description:
Applications of Bayesian inference using software in quantitative biology and genetics. Hierarchical and non-hierarchical models. Model checking, model selection and model comparison. Markov chain Monte Carlo methods.
Interdepartmental With:
Animal Science, Statistics and Probability
Administered By:
Fisheries and Wildlife
Effective Dates:
FS16 - Open


STT 855  Statistical Genetics

Semester:
Fall of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 442 or STT 862
Description:
Probabilistic and statistical methods for genetic linkage and association studies. Quantitative trait locus mapping.
Effective Dates:
FS07 - Open


stt 860  Advanced Inference for Biostatistics

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 861 and (STT 862 or concurrently) or approval of department
Recommended Background:
Masters in statistics or biostatistics
Restrictions:
Open to doctoral students in the Department of Epidemiology and Biostatistics or approval of department.
Description:
Statistical inference problems with biomedical applications.
Interdepartmental With:
Statistics and Probability
Administered By:
Epidemiology
Effective Dates:
SS19 - Open


STT 861  Theory of Probability and Statistics I

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
MTH 234 and MTH 309
Description:
Probability models, random variables and vectors. Special distributions including exponential family. Expected values, covariance matrices, moment generating functions. Convergence in probability and distribution. Weak Law of Large Numbers and Lyapunov Central Limit Theorem.
Effective Dates:
FS10 - Open


STT 862  Theory of Probability and Statistics II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 861
Description:
Statistical inference: sufficiency, estimation, confidence intervals and testing of hypotheses. One and two sample nonparametric tests. Linear models and Gauss-Markov Theorem.
Effective Dates:
SS11 - Open


STT 863  Statistical Methods I

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
(STT 442 or STT 862) and MTH 415
Description:
Introduction to the general theory of linear models. Application of regression models. Interval estimation, prediction and hypothesis testing. Contrasts; model diagnostics; model selection. LASSO type and high dimensional variable selection. Introduction to Linear mixed effect models.
Semester Alias:
STT 841
Effective Dates:
US12 - Open


STT 864  Statistical Methods II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 863
Description:
Generalized linear models(GLMs). Deviance and residual analysis in GLMs. Analysis of two-way and three-way contingency tables. Logistic regression. Log-linear models. Multicategorical response models. Poisson regression. Introduction to generalized estimating equations. Introduction to longitudinal data. Bayesian analysis using WinBUGS.
Effective Dates:
FS13 - Open


stt 866  Spatial Data Analysis

Semester:
Fall of every year
Credits:
Total Credits: 4   Lecture/Recitation/Discussion Hours: 3   Lab Hours: 2
Recommended Background:
(GEO 363 or STT 421 or STT 430) or equivalent quantitative methods courses.
Description:
Theory and techniques for statistical analysis of point patterns, spatially continuous data, and data in spatial zones.
Semester Alias:
GEO 466
Interdepartmental With:
Statistics and Probability
Administered By:
Geography
Effective Dates:
FS17 - Open


STT 867  Linear Model Methodology

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 862
Restrictions:
Open to doctoral students in the Department of Statistics and Probability or approval of department.
Description:
Properties of the multivariate normal distribution, Cochran's Theorem, simple and multiple linear regression models, Gauss-Markov Theorem, best linear unbiased prediction, one- and two-way ANOVA models, sums of squares, diagnostics and model selection, contingency tables and multinomial models, generalized linear models, logistic regression.
Effective Dates:
FS13 - Open


STT 868  Mixed Models: Theory, Methods and Applications

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 867
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Maximum likelihood estimation and other estimation methods for linear mixed models. Statistical properties of LME models. Prediction under LME models. Generalized linear mixed models. Quasi-likelihood estimation, generalized estimating equations for GLMM. Nonlinear mixed models. Diagnostics and influence analysis. Bayesian development in mixed linear models. Application of mixed models.
Effective Dates:
FS13 - Open


STT 872  Statistical Inference I

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 862 and STT 881
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Statistical distributions, decision-theoretic formulation of estimation and testing of hypotheses, sufficiency, Rao-Blackwellization, admissibility, Bayes and minimax estimation, maximum likelihood estimation, inference based on order statistics, Neyman-Pearson Lemma and applications, multiple testing.
Effective Dates:
FS13 - Open


STT 873  Statistical Learning and Data Mining

Semester:
Fall of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 868 and STT 872
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Statistical methods focusing on machine learning and data mining, modern regression and classification techniques, support vector machines, boosting, kernel methods and ensemble methods, clustering dimension reduction, manifold learning, and selected topics.
Effective Dates:
FS13 - Open


STT 874  Introduction to Bayesian Analysis

Semester:
Fall of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 868 and STT 872
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Bayesian methods including empirical Bayes, hierarchical Bayes and nonparametric Bayes, computational methods for Bayesian inference including the Gibbs Sampler and Metropolis-Hastings method, and applications.
Effective Dates:
FS15 - Open


stt 875  R Programming for Data Sciences

Semester:
Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Description:
Programming in R and use of associated open source tools. Addressing practical issues in documenting workflow, data management, and scientific computing.
Interdepartmental With:
Statistics and Probability
Administered By:
Forestry
Effective Dates:
US17 - Open


STT 881  Theory of Probability I

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 861 and MTH 421
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Measures and their extensions, integration. Lp spaces and Inequalities. Lebesgue decomposition, the Radon-Nikodym theorem. Product measures, Fubini's theorem. Kolmogorov consistency theorem. Independence, Kolmogorov's zero-one law, the Borel-Cantelli lemma. Law of large numbers. Central limit theorems, characteristic functions, the Lindeberg-Feller theorem, asymptotic normality of sample median. Poisson convergence. Conditional expectations.
Effective Dates:
FS13 - Open


STT 882  Theory of Probability II

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 881
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Random walks, transcience and recurrence. Martingales, martingale convergence theorem, Doob's inequality, optional stopping theorem. Stationary processes and Ergodic theorem. Brownian motion. Kolmogorov's continuity theorem, strong Markov property, the reflection principle, martingales related to Brownian motion. Weak convergence in C([0,1]) and D([0,1]), Donsker's invariance principle, empirical processes.
Effective Dates:
SS14 - Open


STT 886  Stochastic Processes and Applications

Semester:
Fall of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 441 or STT 861
Description:
Markov chains and their applications in both discrete and continuous time, including classification of states, recurrence, limiting probabilities. Queuing theory, Poisson process and renewal theory.
Effective Dates:
FS00 - Open


STT 888  Stochastic Models in Finance

Semester:
Spring of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 441 or STT 861
Description:
Stochastic models used in pricing financial derivatives. Discrete-time models. Brownian motion. Stochastic integrals and Ito's formula. Basic Black-Scholes model. Risk neutral distribution. European and American options. Exotic options. Interest rate market, futures, and interest rate options.
Semester Alias:
STT 887
Effective Dates:
FS07 - Open


STT 890  Statistical Problems

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 3
Reenrollment Information:
A student may earn a maximum of 24 credits in all enrollments for this course.
Restrictions:
Approval of department.
Description:
Individualized study on selected problems.
Effective Dates:
FS92 - Open


STT 899  Master's Thesis Research

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 6
Reenrollment Information:
A student may earn a maximum of 36 credits in all enrollments for this course.
Restrictions:
Approval of department.
Description:
Master's thesis research.
Effective Dates:
US02 - Open


stt 914  Advanced Organizational Research Methods

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
MGT 906
Description:
Methods for empirically testing scientific theories in organizational contexts.
Interdepartmental With:
Statistics and Probability
Administered By:
Management
Effective Dates:
US11 - Open


stt 920  Advanced Methods in Epidemiology and Applied Statistics

Semester:
Spring of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(EPI 826B or concurrently) or EPI 826 or approval of department
Restrictions:
Open to graduate students in the Department of Epidemiology and Biostatistics or approval of department.
Description:
Pattern recognition and cluster analysis, longitudinal data analysis, path analysis, repeated measures and time-series analysis.
Interdepartmental With:
Statistics and Probability
Administered By:
Epidemiology
Effective Dates:
FS15 - Open


STT 951  Statistical Inference II

Semester:
Spring of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 872 and STT 882
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Decision theoretic estimation: Minimaxity, admissibility, shrinkage estimators, James-Stein estimators. Advanced estimation theory, maximal invariant tests, multiple testing, FDR, and related methods. Permutation and rank tests, unbiasedness and invariance, Hunt Stein theorem.
Effective Dates:
SS13 - Open


STT 953  Asymptotic Theory

Semester:
Spring of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 872 and STT 882
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Locally asymptotic normal models, empirical likelihood, U-statistics, Asymptotically efficient and adaptive procedures
Effective Dates:
SS14 - Open


STT 961  Weak Convergence and Asymptotic Theory

Semester:
Fall of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 872 and STT 882
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Maximal inequalities, covering numbers, symmetrization technique, Glivenko-Cantelli Theorems, Donsker Theorems and some results for Gaussian processes, Vapnik-Chervonenkis classes of sets and functions, applications to M-estimators, bootstrap, delta-method
Effective Dates:
FS13 - Open


STT 964  Stochastic Analysis

Semester:
Spring of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 882
Description:
Stochastic integrals and semi-martingales, Ito formula, stochastic differential equations. Applications.
Effective Dates:
SS95 - Open


STT 990  Problems in Statistics and Probability

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 3
Reenrollment Information:
A student may earn a maximum of 6 credits in all enrollments for this course.
Recommended Background:
STT 872
Restrictions:
Approval of department.
Description:
Individual study on an advanced topic in statistics or probability.
Effective Dates:
FS96 - Open


STT 996  Advanced Topics in Probability

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Reenrollment Information:
A student may earn a maximum of 15 credits in all enrollments for this course.
Recommended Background:
STT 882
Restrictions:
Approval of department.
Description:
Current topics in probability.
Effective Dates:
FS04 - Open


STT 997  Advanced Topics in Statistics

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Reenrollment Information:
A student may earn a maximum of 15 credits in all enrollments for this course.
Recommended Background:
STT 872
Restrictions:
Approval of department.
Description:
Topics selected from non- and semi parametric statistics, multivariate analysis, time series analysis, Bayesian statistics, regression and kernel estimation, and other topics in advanced statistics.
Effective Dates:
FS04 - Open


STT 999  Doctoral Dissertation Research

Semester:
Fall of every year, Spring of every year, Summer of every year
Credits:
Variable from 1 to 24
Reenrollment Information:
A student may earn a maximum of 36 credits in all enrollments for this course.
Restrictions:
Approval of department.
Description:
Doctoral dissertation research.
Effective Dates:
FS14 - Open