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 102 or MTH 103 or MTH 116 or LB 117 or MTH 124 or MTH 132 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:
SS23 - 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 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 - SS23
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.
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.
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
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 301 Computational Methods for Data Science
Semester:
Fall of every year
Credits:
Total Credits: 3 Lecture/Recitation/Discussion Hours: 3
Prerequisite:
(MTH 132 or LB 118 or MTH 152H) and (STT 200 or STT 201 or STT 231 or STT 315 or STT 421 or STT 441)
Description:
Obtaining and managing data using statistical software. Data visualization and graphics. Special challenges in working with high-dimensional data.
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.
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
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 Financial Mathematics for Actuaries II
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:
Evaluate and construct interest rate models. Rational valuation of derivative securities using put-call parity and calculation of European and American options. Risk management techniques using the method of delta-hedging.
Interdepartmental With:
Statistics and Probability
Administered By:
Mathematics
Effective Dates:
FS15 - Open
stt 459 Construction and Evaluation of Actuarial Models
Semester:
Spring of every year
Credits:
Total Credits: 3 Lecture/Recitation/Discussion Hours: 3
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
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.
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
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.
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
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.
Effective Dates:
US12 - Open
STT 864 Statistical Methods II
Semester:
Spring of every year
Credits:
Total Credits: 3 Lecture/Recitation/Discussion Hours: 3
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.
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
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
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
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.
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
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