All Two Terms Ahead Statistics Courses

Fall 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

Jared DiDomenico331
002T R
0800-0915

Paul Fawcett336
003M W F
0900-0950

Xichen Li339
005M W F
1000-1050

Alejandro Gonzalez-Aller329
017M W F
1500-1550

340
007T R
1100-1215

Nina Greenberg34
008T R
1100-1215

Paul Fawcett333
011T R
1230-1345

328
012M W F
1300-1350

Yiming Yang338
013M W F
1400-1450

340
014M W F
1400-1450

340
015T R
1400-1515

Xichen Li339
016T R
1400-1515

334
020M W
1800-1915

Md Rashidul Hasan340
021T R
1830-1945

Pascal Buser338
006M W F
1100-1150

Zheng Tan335
010M W F
1200-1250

Zheng Tan340
018T R
1530-1645

Xin Gao338
009M W F
1200-1250

William Stuart327
004T R
0930-1045

William Brown331
023T R
1630-1745

Lindsey Pittington340Rescheduled from CRN 55352 STAT 145 019.

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
001M W F
1100-1150

Guoyi Zhang318
002T R
1230-1345

Li Li322
003T R
0930-1045

Gabriel Huerta319
004M W
1800-1915

Kellin Rumsey30

STAT 427 - Advanced Data Analysis I

Statistical tools for scientific research, including parametric and non-parametric methods for ANOVA and group comparisons, simple linear and multiple linear regression, and basic ideas of experimental design and analysis. Emphasis placed on the use of statistical packages such as Minitab and SAS. Prerequisite: 145. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
002M W F
0900-0950
Dane Smith Hall 141
James Degnan312
001T R
1230-1345
Science Math Learning Center B59
Yan Lu33

STAT 440 - Regression Analysis

Simple regression and multiple regression. Residual analysis and transformations. Matrix approach to general linear models. Model selection procedures, nonlinear least squares, logistic regression. Computer applications. Prerequisite: 427. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1300-1350

Guoyi Zhang30

STAT 461 - Probability

(Also offered as MATH 441.) Mathematical models for random experiments, random variables, expectation. The common discrete and continuous distributions with application. Joint distributions, conditional probability and expectation, independence. Laws of large numbers and the central limit theorem. Moment generating functions. Prerequisite: MATH 264. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1100-1150

James Degnan33

STAT 472 - Sampling Theory & Practice

Basic methods of survey sampling; simple random sampling, stratified sampling, cluster sampling, systematic sampling and general sampling schemes; estimation based on auxiliary information; design of complex samples and case studies. Prerequisite: **345. {Alternate Falls}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
0930-1045

Yan Lu315

STAT 476 - Multivariate Analysis

Tools for multivariate analysis including multivariate ANOVA, principal components analysis, discriminant analysis, cluster analysis, factor analysis, structural equations modeling, canonical correlations and multidimensional scaling. Prerequisite: 428 or 440. {Offered upon demand}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515

Ronald Christensen313

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
1530-1645

Li Li319

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
001Ronald Christensen1 TO 325
002Erik Erhardt1 TO 325
003 1 TO 325
004Huining Kang1 TO 325
005James Degnan1 TO 325

STAT 527 - Advanced Data Analysis I

Statistical tools for scientific research, including parametric and non-parametric methods for ANOVA and group comparisons, simple linear and multiple linear regression and basic ideas of experimental design and analysis. Emphasis placed on the use of statistical packages such as Minitab and SAS. Course cannot be counted in the hours needed for graduate degrees in Mathematics and Statistics. Prerequisite: 145. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
002M W F
0900-0950
Dane Smith Hall 141
James Degnan317
001T R
1230-1345
Science Math Learning Center B59
Yan Lu311

STAT 540 - Regression Analysis

Simple regression and multiple regression. Residual analysis and transformations. Matrix approach to general linear models. Model selection procedures, nonlinear least squares, logistic regression. Computer applications. Prerequisite: 527. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1300-1350

Guoyi Zhang316

STAT 546 - Theory of Linear Models

Theory of the Linear Models discussed in 440/540 and 445/545. Linear spaces, matrices, projections, multivariate normal distribution and theory of quadratic forms. Non-full rank models and estimability. Gauss-Markov theorem. Distribution theory for normality assumptions. Hypothesis testing and confidence regions. Prerequisite: 553, 545, linear algebra. {Alternate Falls}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1100-1215

Ronald Christensen37

STAT 561 - Probability

Mathematical models for random experiments, random variables, expectation. The common discrete and continuous distributions with application. Joint distributions, conditional probability and expectation, independence. Laws of large numbers and the central limit theorem. Moment generating functions. Prerequisite: MATH 264. {Fall}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1100-1150

James Degnan316

STAT 572 - Sampling Theory & Practice

Basic methods of survey sampling; simple random sampling, stratified sampling, cluster sampling, systematic sampling and general sampling schemes; estimation based on auxiliary information; design of complex samples and case studies. Prerequisite: **345. {Alternate Falls}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
0930-1045

Yan Lu312

STAT 576 - Multivariate Analysis

Tools for multivariate analysis including multivariate ANOVA, principal components analysis, discriminant analysis, cluster analysis, factor analysis, structural equations modeling, canonical correlations and multidimensional scaling. Prerequisite: 528 or 540. {Offered upon demand}

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515

Ronald Christensen33

STAT 579 - Select Topics in Statistics

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1230-1345

Gabriel Huerta311

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
1530-1645

Li Li38

STAT 595 - Problems

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001
-

Erik Erhardt110Statistics Education Practicum

STAT 599 - Masters Thesis

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Ronald Christensen1 TO 625
002Erik Erhardt1 TO 625
003Gabriel Huerta1 TO 625
004Yan Lu1 TO 625
005James Degnan1 TO 625

STAT 605 - Graduate Colloquim

Students present their current research.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Gabriel Huerta10

STAT 649 - Sem Probability & Statistics

(Also offered as MATH 649)

SectionTime/LocationInstructorCreditsSeats OpenNotes
001F
1300-1350
Science Math Learning Center 124
James Degnan112

STAT 650 - Reading and Research

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Yan Lu1 TO 625
002Erik Erhardt1 TO 625
003Li Li1 TO 625
004Ronald Christensen1 TO 625
005Gabriel Huerta1 TO 625
006Guoyi Zhang1 TO 625
007
-

James Degnan1 TO 625

STAT 699 - Dissertation

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001 3 TO 1225
002James Degnan3 TO 1225
003Ronald Christensen3 TO 1225
004Erik Erhardt3 TO 1225
005Yan Lu3 TO 1225
007 3 TO 1225
006Gabriel Huerta3 TO 1225