| COURSE
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| 301: ( 3 credits) Introduction to Statistical Methods |
Techniques in statistical inference; confidence intervals, hypothesis tests, correlation and regression, analysis of variance, chi-square tests.
Prerequisite: college algebra. Credit allowed for only one course: STAT 301, STAT 307/ERHS 307, STAT 315, STAT 311. Text: Statistics: The Exploration and Analysis of Data, 6th ed., by Devore and Peck. This course fulfills a requirement for the Certificate in Applied Statistics.
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| 315: ( 3 credits) Statistics for Engineers and Scientists |
Calculus-based
probability and statistics: distribution theory, estimation,
hypothesis testing, applications to engineering and the sciences.
Prerequisite:
two semesters of college-level calculus. Credit allowed for only one course:
STAT 301, STAT 307/ERHS 307, STAT 315, STAT
311. Text: Probability and Statistics for Engineering and the Sciences 5th (or 6th) ed., Devore. Note: This course was previously numbered STAT 309. This course fulfills a requirement for the Certificate in Applied Statistics.
| 460: ( 3 credits) Applied Multivariate Analysis |
Principles for multivariate estimation and testing; multivariate analysis of variance, discriminant analysis; principal components, factor analysis. Prerequisite: STAT 340 or equivalent undergraduate regression course. Text:
Applied Multivariate Methods for Data Analysts,
Dallas Johnson (ISBN 0-534-23796-7). Please order by ISBN, as the title for this book is often incorrectly given as Applied Multivariate Methods for Data Analysis. Computer Software: R, available for free download. Optional Text: Applied Multivariate Statistical Analysis, 5th ed., Johnson, R.A. and Wichern D.W. This course fulfills a requirement for the Certificate in Applied Statistics. Note: STAT 540 serves as a higher level prerequisite for this course; STAT 512 will work as a prerequisite, provided the student has a good background in matrix theory or linear algebra. |
| 501: ( 1 credit) Statistical Science
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Overview
of statistics; theory; use in agriculture, business, environment,
engineering; modeling; computing; statisticians as researchers/consultants.
No textbook required. This course fulfills a Group I requirement for the MS degree.
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| 511:
( 4 credits) Design & Data Analysis for Researchers, I |
Statistical
methods for experimenters and researchers emphasizing design
and analysis of experiments. Prerequisite:
STAT 301 or STAT 307 or EH/EHCC 307 or STAT 315 (ST309) or
STAT 311 or written consent of instructor. Text: An Introduction to Statistical Methods and Data Analysis 5th ed., Ott & Longnecker. Be sure to get the 5th edition, not the 6th! Computer Software: SAS. For information regarding SAS, click here. No prior knowledge of SAS is assumed, although familiarity with Microsoft Windows and an internet browser (Firefox, Netscape or Internet Explorer) is expected. This course fulfills a requirement for the Certificate in Applied Statistics. |
| 512:
( 4 credits) Design & Data Analysis for Researchers, II
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Model building
and decision making; communication of statistical information. Prerequisite:
STAT 511. Text: An Introduction to Statistical Methods and Data Analysis, 5th ed., Ott & Longnecker. Be sure to get the 5th edition, not the 6th! Computer Software: SAS. For information regarding SAS, click here. See prerequisite ST511. This course fulfills a requirement for the Certificate in Applied Statistics.
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| 520:
( 4 credits) Introduction to Probability Theory |
Probability,
random variables, distributions, expectations, generating functions,
limit theorems, convergence, random processes. Prerequisites:
MATH 229 - Matrices and Linear Equations (to be replaced with MATH 369 - Linear Algebra), MATH 261 - Calculus III, and MATH 317 - Advanced Calculus. Text: Probability and Random Processes, 3rd ed., Grimmett & Stirzaker. Please contact the Distance Degree Program Coordinator, Jana Anderson, before registering for this course if you have any doubts about having the needed prerequisites. This course fulfills a Group I requirement for the MS degree, as well as a requirement for the Certificate in Statistical Theory & Methods.
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| 521:
( 3 credits) Stochastic Processes I |
Characterization
of stochastic processes, Markov chains in discrete and continuous
time, branching processes, renewal theory, Brownian motion. Prerequisite:
STAT 520. Text: An Introduction to Stochastic Modeling, 3rd ed., Taylor & Karlin. This course fulfills a Group II or III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
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| 523:
( 3 credits) Quantitative Spatial Analysis |
Techniques
in spatial analysis: point pattern analysis, spatial autocorrelation,
trend surface and spectral analysis. Prerequisite:
STAT 301 or STAT 307 or EH/EHCC 307. Credit not allowed
for both STAT 523 and NR 523. Text: Course manual entitled "Quantitative Spatial Statistics", available through CSU Bookstore. Computer Software: R, available for free download. This course fulfills a Group III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods and Applied Statistics certificates.
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| 525: ( 3 credits) Analysis of Time Series I |
Trend and
seasonality, stationary processes, Hilbert space techniques,
spectral distribution function, fitting ARIMA models, linear
prediction. Prerequisite:
STAT 430. STAT 530 works as a "higher level" prerequisite for this course. Text: Introduction to Time Series and Forecasting, Brockwell & Davis. Computer Software: Contained in the text. This course fulfills a Group II or III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
| 526: ( 3 credits) Analysis of Time Series II |
Spectral analysis; the periodogram; spectral estimation techniques; multivariate time series; linear systems and optimal control; Kalman filtering and prediction. Prerequisite:
STAT 525. Text: Time Series: Theory and Methods, 2nd ed., Brockwell & Davis. Computer Software: available through instructor. This course fulfills a Group III requirement for the MS degree.
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| 530: ( 3 credits) Mathematical Statistics |
Sampling
distributions, estimation, testing, confidence intervals; exact
and asymptotic theories of maximum likelihood and distribution-free
methods. Prerequisite:
STAT 520. Text: Statistical Inference, 2nd ed., Casella & Berger. This course fulfills a Group I requirement for the MS degree, as well as fulfilling a requirement for the Statistical Theory & Methods certificate.
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| 540:
( 3 credits) Data Analysis and Regression |
Introduction
to multiple regression and data analysis with emphasis on graphics
and computing. Prerequisite: Six credits of upper-division statistics courses or written consent of instructor. Some knowledge of linear algebra highly recommended. Text: Applied Linear Statistical Models, 5th ed., Kutner, Nachtsheim, Neter & Li . Computer Software: R. Students will be given instructions in class on downloading and using this software. This course fulfills a Group I requirement for the MS degree, as well as fulfilling a requirement for the Applied Statistics and Statistical Theory & Methods certificates.
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| 547: ( 3 credits) Statistics for Environmental Monitoring |
Applications
of statistics in environmental pollution studies involving air,
water, or soil monitoring; sampling designs; trend analysis;
censored data. Prerequisite:
ST/STCC 301. Credit not allowed for both STAT 547 and CIVE 547. Text: Statistical Methods for Environmental Pollution Monitoring, Gilbert & Reinhold. This course serves as an elective for the Applied Statistics and the Statistical Theory & Methods certificates. Does not count toward requirements for the MS degree in Statistics. Note: This course offers topics that are useful in a number of application areas. For a complete list of topics covered, please contact Dr. Anderson.
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| 560: ( 3 credits) Applied Multivariate Analysis |
Multivariate analysis of variance; principal components; factor analysis; discriminate analysis; cluster analysis. Prerequisite:
STAT 520, STAT 540. Text: Applied Multivariate Methods for Data Analysts, Dallas Johnson (ISBN 0-534-23796-7). Please order by ISBN, as the title for this book is often incorrectly given as Applied Multivariate Methods for Data Analysis. Computer Software: R (freeware version of S-Plus). Optional Text: Applied Multivariate Statistical Analysis, 5th ed., Johnson, R.A. and Wichern D.W. This course fulfills a Group III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
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| 570:
( 3 credits) Nonparametric Statistics |
Distribution and uses of order statistics; nonparametric inferential techniques, their uses and mathematical properties. Prerequisite:
STAT 430 or written consent of instructor. STAT 530 works as a "higher level" prerequisite for this course. Text: Introduction to Modern Nonparametric Statistics, Higgins. Computer Software: R (freeware version of S-Plus). This course fulfills a Group III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
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| 586: ( 1 credit) Practicum in Consulting Techniques |
Instruction
on planning studies, writing reports, and interacting with clients.
Attend and critique consulting sessions. Prerequisite:
STAT 540. This course fulfills a Group I requirement for the MS degree.
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| 600:
( 3 credits) Statistical Computing |
Statistical
packages; graphical data presentation; model fitting and diagnostics;
random numbers; simulation; numerical methods in statistics. Prerequisite:
STAT 520, STAT 540. This course fulfills a Group III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
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| 605:
( 3 credits) Theory of Sampling Techniques |
Survey designs;
simple random, stratified, cluster samples; theory of estimation;
optimization techniques for minimum variance or costs. Prerequisites: (see note below) [STAT 301 or STAT 307 or EH/ EHCC 307 or STAT 315 (ST309) or STAT 311] and STAT 430. Text: Model Assisted Survey Sampling, by Särndal, Swensson & Wretman. Computer Software: SAS and either S-Plus or R, plus possibly specialized software which will be provided. For information regarding SAS, click here. This course fulfills a Group II or III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate. Note: It is highly recommended that students take STAT 530 prior to or concurrent with STAT 605.
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| 640: ( 4 credits) Design and Linear Modeling I |
Introduction to linear models; experimental design; fixed, random, and mixed models. Prerequisite: STAT 540. Text: Course notes will be provided. Some texts will be suggested for reference. Computer Software: SAS. For information regarding SAS, click here. This course fulfills a Group I requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate. Note: It is highly recommended that students take STAT 530 prior to or concurrent with STAT 640.
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| 645:
( 3 credits) Categorical Data Analysis and GLIM |
Generalized
linear models, binary and polytomous data, log linear models,
quasilikelihood models, survival data models. Co-requisite:
STAT 640. Text: Categorical Data Analysis, 2nd ed., Alan Agresti, ISBN: 0-471-36093-7 Computer Software: SAS and R. You will receive information on obtaining SAS at a discounted student rate a few days before the semester begins. R is available by free download. This course fulfills a Group III requirement for the MS degree. Note: Although STAT 640 is listed as a co-requisite, it is highly recommended that students complete STAT 640 prior to taking STAT 645.
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| 650:
( 3 credits) Design and Linear Modeling II |
Mixed factorials;
response surface methodology; Taguchi methods; variance components. Prerequisite:
STAT 640 or written consent of instructor. Texts: Course notes will be provided. Some texts will be suggested for reference. Software: SAS. For information regarding SAS, click here. This course fulfills a Group II or III requirement for the MS degree.
| 675K: ( 3 credits) Bayesian Statistics |
Bayesian inference and theory, hierarchical models, Markov chain Monte Carlo theory and methods, model criticism and selection, hierarchical regression and generalized linear models, and other topics. Prerequisites: STAT 430 is the prerequisite for this course, however it is recommended that student has had STAT 530 and STAT 540. Text: Bayesian Data Analysis, 2nd ed., Gelman, Carlin, Stern & Rubin. Computer Software: S-Plus or R, and WinBUGS (freeware - more information will be provided on the course web page). This course fulfills a Group III requirement for the MS degree, as well as serving as an elective for the Statistical Theory & Methods certificate.
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| 699: ( Variable credit) Thesis |
Student must have an advisor for their project or thesis before registering for this class. Ideally you
should start this before your final semester. This course fulfills a Group I requirement for the MS degree.
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