Department of Mathematics & Statistics

Campus Address:
University of New Mexico
Department of Mathematics and Statistics
1 University of New Mexico, MSC01 1115
Albuquerque, NM 87131

Physical Address:
University of New Mexico
Department of Mathematics and Statistics
311 Terrace Street NE, Room 389
Albuquerque, NM 87106

Phone: (505) 277-4613
Fax: (505) 277-0988

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

Click on course title for full details

STAT 279 - T: Introductory Statistics
Offered upon demand.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1100-1150 Dane Smith Hall 226	James Degnan	3	20

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.
Section	Time/Location	Instructor	Credits	Seats Open
001	T R 1230-1345 Dane Smith Hall 226	Li Li	3	9
002	M W F 1000-1050 Dane Smith Hall 228	Zacharia Stuart	3	3
003	T R 1630-1745 Dane Smith Hall 333	Kellin Rumsey	3	5
005	-		3	0

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.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	T R 1530-1645 Collaborative Teaching & Learn 300	Erik Erhardt	3	22	Interactive 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}
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1300-1350 Dane Smith Hall 328	Guoyi Zhang	3	10

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.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1200-1250 Dane Smith Hall 328	James Degnan	3	7

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}
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1100-1150 Dane Smith Hall 127	Guoyi Zhang	3	24

STAT 495 - Individual Study
Guided study, under the supervision of a faculty member, of selected topics not covered in regular course offerings.
Section	Instructor	Credits	Seats Open
001	Ronald Christensen	1 TO 3	25
002	Erik Erhardt	1 TO 3	25
003	Charles Wiggins	1 TO 3	25
004	Huining Kang	1 TO 3	25
005	James Degnan	1 TO 3	25

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.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	T R 1530-1645 Collaborative Teaching & Learn 300	Erik Erhardt	3	6	Interactive 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}
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1300-1350 Dane Smith Hall 328	Guoyi Zhang	3	2

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}
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	T R 1100-1215 Dane Smith Hall 233	Ronald Christensen	3	14

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.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1200-1250 Dane Smith Hall 328	James Degnan	3	0

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}
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	M W F 1100-1150 Dane Smith Hall 127	Guoyi Zhang	3	6

STAT 579 - Sel T:
.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	T R 1400-1515 Science Math Learning Center 356	Fletcher Christensen	3	4

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.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	T R 0930-1045 Science Math Learning Center 356	Li Li	3	7

STAT 595 - Problems
.
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	-	Erik Erhardt	1	10

STAT 599 - Masters Thesis
Offered on a CR/NC basis only.
Section	Time/Location	Instructor	Credits	Seats Open
001		Ronald Christensen	1 TO 6	25
002		Erik Erhardt	1 TO 6	23
003		Gabriel Huerta	1 TO 6	25
004		Yan Lu	1 TO 6	25
005		James Degnan	1 TO 6	23
006	-	Fletcher Christensen	1 TO 6	9
007	-	Li Li	1 TO 6	7

STAT 649 - Sem Probability & Statistics
(Also offered as MATH 649)
Section	Time/Location	Instructor	Credits	Seats Open	Notes
001	F 1300-1350 Science Math Learning Center 124	James Degnan	1	10

STAT 650 - Reading and Research
.
Section	Time/Location	Instructor	Credits	Seats Open
001		Yan Lu	1 TO 6	24
002		Huining Kang	1 TO 6	23
003		Li Li	1 TO 6	25
004		Ronald Christensen	1 TO 6	25
005		Li Luo	1 TO 6	24
006		Guoyi Zhang	1 TO 6	24
007	-	James Degnan	1 TO 6	23
008	-	Fletcher Christensen	1 TO 6	7

STAT 699 - Dissertation
Offered on a CR/NC basis only.
Section	Instructor	Credits	Seats Open
001		3 TO 12	25
002	James Degnan	3 TO 12	22
003	Ronald Christensen	3 TO 12	25
004	Erik Erhardt	3 TO 12	24
005	Yan Lu	3 TO 12	24
007	Li Li	3 TO 12	24
006	Gabriel Huerta	3 TO 12	24

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Department of Mathematics & Statistics

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All Current Term Statistics Courses

Fall 2019

STAT 279 - T: Introductory Statistics

STAT 345 - Elements of Math Stat & Prob

STAT 427 - Advanced Data Analysis I

STAT 440 - Regression Analysis

STAT 461 - Probability

STAT 472 - Sampling Theory & Practice

STAT 495 - Individual Study

STAT 527 - Advanced Data Analysis I

STAT 540 - Regression Analysis

STAT 546 - Theory of Linear Models

STAT 561 - Probability

STAT 572 - Sampling Theory & Practice

STAT 579 - Sel T:

STAT 590 - Statistical Computing

STAT 595 - Problems

STAT 599 - Masters Thesis

STAT 649 - Sem Probability & Statistics

STAT 650 - Reading and Research

STAT 699 - Dissertation