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All Current Term Statistics Courses


Fall 2019

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 279 - T: Introductory Statistics

Offered upon demand.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1100-1150
Dane Smith Hall 226
James Degnan320

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
001T R
1230-1345
Dane Smith Hall 226
Li Li33
002M W F
1000-1050
Dane Smith Hall 228
Zacharia Stuart30
003T R
1630-1745
Dane Smith Hall 333
Kellin Rumsey30
005
-

30

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: MATH 1350.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1530-1645
Collaborative Teaching & Learn 300
Erik Erhardt315Interactive Learning Space: http://goto.unm.edu/vuq4a

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
Dane Smith Hall 328
Guoyi Zhang310

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 2530.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1200-1250
Dane Smith Hall 328
James Degnan36

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
001M W F
1100-1150
Dane Smith Hall 127
Guoyi Zhang322

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
003Charles Wiggins1 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: MATH 1350.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1530-1645
Collaborative Teaching & Learn 300
Erik Erhardt33Interactive Learning Space: http://goto.unm.edu/vuq4a

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
Dane Smith Hall 328
Guoyi Zhang31

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
Dane Smith Hall 233
Ronald Christensen313

STAT 561 - 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 2530.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001M W F
1200-1250
Dane Smith Hall 328
James Degnan30

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
001M W F
1100-1150
Dane Smith Hall 127
Guoyi Zhang36

STAT 579 - Sel T:

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
1400-1515
Science Math Learning Center 356
Fletcher Christensen34

STAT 590 - Statistical Computing

A detailed examination of essential statistical computing skills needed for research and industrial work. Students will use S-Plus, Matlab and SAS to develop algorithms for solving a variety of statistical problems using resampling and simulation techniques such as the bootstrap, Monte Carlo methods and Markov chain methods for approximating probability distributions. Applications to linear and non-linear models will be stressed. Prerequisite: 528.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001T R
0930-1045
Science Math Learning Center 356
Li Li37

STAT 595 - Problems

.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001
-

Erik Erhardt110

STAT 599 - Masters Thesis

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001Ronald Christensen1 TO 625
002Erik Erhardt1 TO 623
003Gabriel Huerta1 TO 625
004Yan Lu1 TO 625
005James Degnan1 TO 623
006
-

Fletcher Christensen1 TO 69
007
-

Li Li1 TO 67

STAT 649 - Sem Probability & Statistics

(Also offered as MATH 649)

SectionTime/LocationInstructorCreditsSeats OpenNotes
001F
1300-1350
Science Math Learning Center 124
James Degnan110

STAT 650 - Reading and Research

.

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

James Degnan1 TO 623
008
-

Fletcher Christensen1 TO 67

STAT 699 - Dissertation

Offered on a CR/NC basis only.

SectionTime/LocationInstructorCreditsSeats OpenNotes
001 3 TO 1225
002James Degnan3 TO 1222
003Ronald Christensen3 TO 1225
004Erik Erhardt3 TO 1224
005Yan Lu3 TO 1224
007Li Li3 TO 1224
006Gabriel Huerta3 TO 1224