All Current Term Statistics Courses

Spring 2017

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 145 - Intro To Statistics

Techniques for the visual presentation of numerical data, descriptive statistics, introduction to probability and basic probability models used in statistics, introduction to sampling and statistical inference, illustrated by examples from a variety of fields. Meets New Mexico Lower-Division General Education Common Core Curriculum Area II: Mathematics (NMCCN 1113). Prerequisite: (MATH 101 and MATH 102) or (MATH 118 and MATH 119) or MATH 120 or MATH 121 or MATH 123 or MATH 150 or MATH 162 or MATH 163 or MATH 180 or MATH 181 or MATH 264 or ACT Math =>22 or SAT Math Section =>540 or ACCUPLACER Elementary Algebra =66-103 or ACCUPLACER College-Level Math =37-68. {Summer, Fall, Spring}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
0800-0850
Dane Smith Hall 129
Jared DiDomenico36
002T R
0800-0915
Dane Smith Hall 225
Igor Litvinovich37
003M W F
0900-0950
Dane Smith Hall 228
Alejandro Gonzalez-Aller32
004T R
0930-1045
Dane Smith Hall 324
Paul Fawcett37
006M W F
1000-1050
Dane Smith Hall 234
Ryan Kowal310
014M W F
1200-1250
Dane Smith Hall 226
Zheng Tan320
010T R
1100-1215
Dane Smith Hall 329
Erik Erhardt31
005T R
0930-1045
Dane Smith Hall 228
Lindsey Pittington32
015T R
1230-1345
Dane Smith Hall 129
Xin Gao38
016M W F
1300-1350
Dane Smith Hall 226
Zheng Tan321
017M W F
1400-1450
Dane Smith Hall 129
Guoyi Zhang323
019M W F
1500-1550
Dane Smith Hall 129
William Stuart320
011T R
1100-1215
Dane Smith Hall 127
Nina Greenberg32
018T R
1400-1515
Dane Smith Hall 223
William Brown37
023M W
1730-1845
Dane Smith Hall 229
Pascal Buser317
012M W F
1200-1250
Dane Smith Hall 223
Alejandro Gonzalez-Aller32
024T R
1900-2015
Dane Smith Hall 136
Kellin Rumsey32
013M W F
1200-1250
Dane Smith Hall 228
Md Rashidul Hasan312
007M W F
1000-1050
Dane Smith Hall 129
Paul Fawcett34
021T R
1600-1715
Dane Smith Hall 226
Huan Yu334
009M W F
1100-1150
Dane Smith Hall 223
Alejandro Gonzalez-Aller34
008M W F
1100-1150
Dane Smith Hall 226
Ryan Kowal32
022T R
1600-1830
Dane Smith Hall 227
Ryan Kowal310
020T R
1530-1645
Dane Smith Hall 127
Yan Lu311

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 163 or MATH 181.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002T R
1230-1345
Dane Smith Hall 127
Gabriel Huerta30
001M W F
1100-1150
Dane Smith Hall 225
Ayed Alanzi30
003T R
1400-1515
Dane Smith Hall 129
Li Li31

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 Erhardt313

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
1100-1150
Science Math Learning Center 352
Guoyi Zhang33

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
0900-0950
Science Math Learning Center 120
James Degnan311

STAT 470 - Industrial Statistics

Basic ideas of statistical quality control and improvement. Topics covered: Deming's 14 points and deadly diseases, Pareto charts, histograms, cause and effect diagrams, control charts, sampling, prediction, reliability, experimental design, fractional factorials, Taguchi methods, response surfaces. Prerequisite: **345.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215
Sara Raynolds Hall 107
Ronald Christensen311

STAT 474 - Bio Statistics

A detailed overview of methods commonly used to analyze medical and epidemiological data. Topics include the Kaplan-Meier estimate of the survivor function, models for censored survival data, the Cox proportional hazards model, methods for categorical response data including logistic regression and probit analysis, generalized linear models. Prerequisite: 428 or 440.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1000-1050
Science Math Learning Center 352
James Degnan321

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: 461 and (427 or 440). {Alternate Springs}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215
Sara Raynolds Hall 101
Li Li38

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
001Erik Erhardt1 TO 323
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 Erhardt38

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
1100-1150
Science Math Learning Center 352
Guoyi Zhang32

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
0900-0950
Science Math Learning Center 120
James Degnan34

STAT 557 - Adv Statistical Inference II

Standard limit theorems, hypothesis testing, confidence intervals and decision theory. Prerequisite: 556. {Alternate Springs}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515
Science Math Learning Center 352
Ronald Christensen315

STAT 565 - Stochastic Processes with Apps

(Also offered as MATH 540) Markov chains and processes with applications. Classification of states. Decompositions. Stationary distributions. Probability of absorption, the gambler's ruin and mean time problems. Queuing and branching processes. Introduction to continuous time Markov processes. Jump processes and Brownian motion. Prerequisite: 561. {Offered on demand}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1230-1345
Science Math Learning Center 356
Yan Lu313

STAT 570 - Industrial Stat

Basic ideas of statistical quality control and improvement. Topics covered: Demings 14 points and deadly diseases, Pareto charts, histograms, cause and effect diagrams, control charts, sampling, prediction, reliability, experimental design, fractional factorials, Taguchi methods, response surfaces. Prerequisite: **345.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215
Sara Raynolds Hall 107
Ronald Christensen33

STAT 574 - Bio Statistics

A detailed overview of methods commonly used to analyze medical and epidemiological data. Topics include the Kaplan-Meier estimate of the survivor function, models for censored survival data, the Cox proportional hazards model, methods for categorical response data including logistic regression and probit analysis, generalized linear models. Prerequisite: 528 or 540.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1000-1050
Science Math Learning Center 352
James Degnan316

STAT 577 - Intro to 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: 561 and (527 or 540). {Alternate Springs}.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215
Sara Raynolds Hall 101
Li Li311

STAT 579 - Select Topics in Statistics

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002T R
0930-1045
Dane Smith Hall 128
Gabriel Huerta32

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

STAT 595 - Problems

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001
-

Erik Erhardt19

STAT 599 - Masters Thesis

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Yan Lu1 TO 624
002Ronald Christensen1 TO 625
003Erik Erhardt1 TO 624
004Gabriel Huerta1 TO 625
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 625
003Erik Erhardt1 TO 625
004Ronald Christensen1 TO 625
005Huining Kang1 TO 624
006Gabriel Huerta1 TO 624
007Guoyi Zhang1 TO 625

STAT 699 - Dissertation

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
002Ronald Christensen3 TO 1223
003Gabriel Huerta3 TO 1224
004Erik Erhardt3 TO 1225
005 3 TO 1225
007James Degnan3 TO 1221
006Yan Lu3 TO 1225