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All Next Term Statistics Courses


Spring 2020

This data is offered for your convenience only. The schedule data is updated regularly and may not reflect recent changes to the Schedule of Classes. For full, up-to-date course information please contact the Registrar's office

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STAT 345 - Elements of Math Stat & Prob

An introduction to probability including combinatorics, Bayes' theorem, probability densities, expectation, variance and correlation. An introduction to estimation, confidence intervals and hypothesis testing. Prerequisite: MATH 1440 or MATH 1522.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002T R
1230-1345
Mitchell Hall 102
Fletcher Christensen350
001M W F
0900-0950
Dane Smith Hall 225
Anastasiia Kim30
003T R
1400-1515
Dane Smith Hall 127
Kellin Rumsey30

STAT 428 - Advanced Data Analysis II

A continuation of 427 that focuses on methods for analyzing multivariate data and categorical data. Topics include MANOVA, principal components, discriminant analysis, classification, factor analysis, analysis of contingency tables including log-linear models for multidimensional tables and logistic regression. Prerequisite: 427.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1530-1645
Collaborative Teaching & Learn 300
Erik Erhardt334Interactive Learning Space

STAT 445 - Analysis of Variance Design

A data-analytic course. Multifactor ANOVA. Principles of experimental design. Analysis of randomized blocks, Latin squares, split plots, etc. Random and mixed models. Extensive use of computer packages with interpretation, diagnostics. Prerequisite: 440. {Spring}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1300-1350
Science Math Learning Center 120
Yan Lu39

STAT 453 - Statistical Inference with App

Transformations of univariate and multivariate distributions to obtain the special distributions important in statistics. Concepts of estimation and hypothesis testing in both large and small samples with emphasis on the statistical properties of the more commonly used procedures, including student's t-tests, F-tests and chi-square tests. Confidence intervals. Performance of procedures under non-standard conditions (i.e., robustness). Prerequisite: 461. {Spring}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1100-1150
Science Math Learning Center 120
Yan Lu312

STAT 477 - Intro Bayes Modeling

An introduction to Bayesian methodology and applications. Topics covered include: probability review, Bayes' theorem, prior elicitation, Markov chain Monte Carlo techniques. The free software programs WinBUGS and R will be used for data analysis. Prerequisite: (427 or 440) and 461.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515
Dane Smith Hall 334
Fletcher Christensen315

STAT 479 - Topics in Statistics

Modern topics not covered in regular course offerings.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215
Dane Smith Hall 129
Ronald Christensen319

STAT 481 - Intro to Time Series Analysis

Introduction to time domain and frequency domain models of time series. Data analysis with emphasis on Box-Jenkins methods. Topics such as multivariate models; linear filters; linear prediction; forecasting and control. Prerequisite: 461. {Alternate Springs}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
0930-1045
Science Math Learning Center 352
Li Li326

STAT 495 - Individual Study

Guided study, under the supervision of a faculty member, of selected topics not covered in regular course offerings.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002James Degnan1 TO 325
003Ronald Christensen1 TO 325
004
-

Erik Erhardt1 TO 325

STAT 528 - Advanced Data Analysis II

A continuation of 527 that focuses on methods for analyzing multivariate data and categorical data. Topics include MANOVA, principal components, discriminate analysis, classification, factor analysis, analysis of contingency tables including log-linear models for multidimensional tables and logistic regression. Prerequisite: 527.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1530-1645
Collaborative Teaching & Learn 300
Erik Erhardt343Interactive Learning Space

STAT 545 - Analysis of Variance Design

A data-analytic course. Multifactor ANOVA. Principles of experimental design. Analysis of randomized blocks, Latin squares, split plots, etc. Random and mixed models. Extensive use of computer packages with interpretation, diagnostics. Prerequisite: 540. {Spring}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1300-1350
Science Math Learning Center 120
Yan Lu32

STAT 547 - Multivariate Analysis

Hotelling T2, multivariate ANOVA and Regression, classification and discrimination, principal components and factor analysis, clustering, graphical and computational techniques, topics in linear models. Prerequisite: 546. {Alternate Springs}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515
Science Math Learning Center 352
Ronald Christensen33

STAT 553 - Statistical Inference with App

Transformations of univariate and multivariate distributions to obtain the special distributions important in statistics. Concepts of estimation and hypothesis testing in both large and small samples with emphasis on the statistical properties of the more commonly used procedures, including Students t-tests, F-tests and chi-square tests. Confidence intervals. Performance of procedures under non-standard conditions (i.e., robustness). Prerequisite: 561. {Spring}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1100-1150
Science Math Learning Center 120
Yan Lu31

STAT 577 - Intro Bayseian Modeling

An introduction to Bayesian methodology and applications. Topics covered include: probability review, Bayes' theorem, prior elicitation, Markov chain Monte Carlo techniques. The free software programs WinBUGS and R will be used for data analysis. Prerequisite: (527 or 540) and 561.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515
Dane Smith Hall 334
Fletcher Christensen31

STAT 579 - Sel T:

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1700-1815
Science Math Learning Center 356
Gabriel Huerta321
002T R
1100-1215
Dane Smith Hall 129
Ronald Christensen32

STAT 581 - Introduction to Time Series

Introduction to time domain and frequency domain models of time series. Data analysis with emphasis on Box-Jenkins methods. Topics such as multivariate models; linear filters; linear prediction; forecasting and control. Prerequisite: 561. {Alternate Springs}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
0930-1045
Science Math Learning Center 352
Li Li32

STAT 586 - Nonparametric Curve Estimate

Nonparametric regression, density estimation, filtering, spectral density estimation, image reconstruction and pattern recognition. Tools include orthogonal series, kernels, splines, wavelets and neural networks. Applications to medicine, engineering, biostatistics and economics. Prerequisite: 561. {Offered upon demand}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1230-1345
Science Math Learning Center 356
Guoyi Zhang325rescheduled from CRN 52964 STAT 579 003.

STAT 599 - Masters Thesis

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Yan Lu1 TO 625
002Ronald Christensen1 TO 625
003Erik Erhardt1 TO 624
004Li Li1 TO 624
005James Degnan1 TO 625
006
-

Guoyi Zhang1 TO 62

STAT 649 - Sem Probability & Statistics

(Also offered as MATH 649)

SectionTime/LocationInstructorCreditsSeats OpenNotes
002
-

James Degnan15

STAT 650 - Reading and Research

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Yan Lu1 TO 625
002James Degnan1 TO 623
003Li Li1 TO 625
004Ronald Christensen1 TO 625
005Li Luo1 TO 624
006Huining Kang1 TO 625
007Guoyi Zhang1 TO 625

STAT 699 - Dissertation

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002Ronald Christensen3 TO 1225
003Gabriel Huerta3 TO 1225
004Erik Erhardt3 TO 1225
005Li Li3 TO 1225
007James Degnan3 TO 1224
006Yan Lu3 TO 1225
008
-

Gabriel Huerta3 TO 122