CATALOG DESCRIPTIONS OF UAF STATISTICS COURSES
STAT 200 3 credits Elementary Probability and Statistics Fairbanks Fall, Spring, Summer
Descriptive statistics, frequency distributions, sampling distributions, elementary probability, estimation of population parameters, hypothesis testing (one and two sample problems), correlation, simple linear regression, and one-way analysis of variance. Parametric and nonparametric methods. Materials fee: $10.00. (Prerequisites: MATH 107, 161, 181 or consent of instructor) Juneau equivalent course is STAT 373. Example text: Practical Statistics by Moore and McCabe.
3 credits Statistics Fairbanks Spring
A calculus-based course emphasizing applications. Topics include probability, point and interval estimation including maximum likelihood, one and two sample hypothesis test including likelihood ratio tests, simple linear regression, and one-way analysis of variance. A student may not use STAT 200 and 300 to meet the requirement of a year's sequence course in statistics. (Prerequisites: MATH 200, 262, 272 or equivalent). Example text:
4 credits Regression and Analysis of Variance Fairbanks Fall, Spring
A thorough study of multiple regression including multiple and partial correlation, the extra sums of squares principle, indicator variables, and model selection techniques. Analysis of variance and covariance for multifactor studies in completely randomized and randomized complete block designs, multiple comparisons, and orthogonal contrasts. Materials fee: $10.00. (Prerequisites: STAT 200 [STAT 373-J] or STAT 300 or consent of instructor.) Course is offered as 3 lecture hours and a 3 hour computer lab. Example text: Applied Linear Statistical Models by Neter, Wasserman, and Kutner.
3 credits Scientific Sampling Fairbanks Fall
Sampling methods, including simple random, stratified and systematic; estimation procedures, including ratio and regression methods; special area and point sampling procedures; optimum allocation. Materials fee: $10.00. (Prerequisites: STAT 200 or 300 or consent of instructor.) Example text: Elementary Survey Sampling by Schaeffer, Mendenhall, and Ott supplemented by handouts.
3 credits Applied Multivariate Statistics Alternate Spring
Estimation and hypothesis testing, multivariate normality and its assessment, multivariate one and two sample tests, confidence regions, multivariate analysis of variance, discrimination and classification, principal components, factor analysis, clustering techniques, and graphical presentation. Statistical computing packages utilized in assignments. (Prerequisite: STAT 401 or consent of instructor.) Example text: Applied Multivariate Statistics by Johnson and Wichern.
3 credits Experimental Design Fairbanks Alternate Spring
Constructing and analyzing designs for experimental investigations; completely randomized, randomized complete block and Latin-square designs, split-plot designs, incomplete block designs, confounded factorial designs, nested designs, treatment of missing data, comparison of designs. (Prerequisites: STAT 401 or permission of instructor). Example text: Experimental Design by Montgomery
3 credits Spatial Statistics Fairbanks As Demand Warrants
Stochastic processes. Geostatistics including kriging and spatial design of experiments. Point processes including model selection and K-functions. Lattice process models and image analysis. Computer intensive statistical methods. (Prerequisites: STAT 401 and MATH 202 or permission of instructor.) Example text: Statistics for Spatial Data by Cressie.
3 credits Time Series Fairbanks As Demand Warrants
An applied course in time series and repeated measure analysis. Autoregression and moving average models. Estimation of parameters and tests. Prediction. Spectral analysis. (Prerequisites: STAT 401 or permission of instructor.) Example text: Time Series by Kendall and Ord.
3 credits Distribution-Free Statistics Fairbanks As Demand Warrants
Methods for distribution-free (non-parametric) statistical estimation and testing. These methods apply to many practical situations including small samples and non-Gaussian error structures. Univariate, bivariate, and multivariate tests will be presented and illustrated using a variety of applications and data sets. (Prerequisites: STAT 200 (Juneau STAT 373); STAT 401 recommended, or permission of instructor). Example text: Practical Nonparametric Statistics by Conover.
3 credits Categorical Data Analysis Fairbanks Alternate Fall
Statistical methods designed for count and categorical data. Contingency tables. Logistic and related models. Loglinear models. Repeated categorical responses. Survival data. (Prerequisites: STAT 401 or permission of instructor). Example text: Categorical Data Analysis by Agresti.
3 credits Exploratory Data Analysis Fairbanks & Juneau As Demand Warrants
Quantitative and graphical methods for explaining data and for presenting data to others. Computer-aided detection and analysis of patterns in data. Methods for analysis of patterns in data. methods for validating the assumptions of common statistical tests and models. Use of computer graphics in statistical analysis. (Prerequisite: STAT 200 (Juneau STAT 373); STAT 401 recommended). Example text: Typically a text by Tukey.
3 credits Statistical Theory I - Probability and Sampling Distributions Fairbanks Fal
Probability, distributions of random variables, conditional probability and stochastic independence, distributions of functions of random variables, expectation, limiting distributions, moment generating functions, distributions derived from the normal distributions. (Prerequisites: MATH 202, MATH 314, STAT 200, 300, or MATH 371, STAT 401 recommended.) Example text: Mathematical Statistics and Data Analysis by Rice.
3 credits Statistical Theory II - Estimation and Hypothesis Testing Fairbanks Spring
Estimation of parameters including evaluation of efficiency and sufficiency, maximum likelihood and method of moments estimation, bootstrap and other resampling techniques to estimate variances, and construction of confidence intervals. Hypothesis testing including the Neyman-Pearson paradigm and likelihood ratio tests for evaluating one and two sample problems, the analysis of categorical data, and analysis of variance problems. Frequentist and Bayesian inference. (Prerequisites: STAT 651.) Example text: Mathematical Statistics and Data Analysis by Rice.
3 credits Statistical Theory III - Linear Models Fairbanks Fall
Best linear unbiased estimation, Gauss-Markov theory and applications, maximum likelihood estimation for linear models, multivariate normal distributions, linear regression and analysis of variance, weighted regression, robust and nonlinear regression, logistic regression, Poisson regression, ridge regression, smoothing, simple time domain models. (Prerequisites: STAT 652 or MATH 408 and STAT 401 and MATH 314.) Example text: An Introduction to Computational Statistics: Regression Analysis by Jennrich.
1 credit Consulting Seminar Fairbanks Spring
Topics related to recent consulting problems. Students will be involved in consulting for other graduate students and faculty and in learning about consulting practices. (Prerequisite: admission into the interdisciplinary graduate program in statistics). May be repeated for credit up to 3 credits. Example text: none.
3 credits Sampling Theory Fairbanks Alternate Spring
Statistical theory for sampling and sample surveys. Choice of method, power, and sample size considerations, treatment of sampling and non-sampling biases. Sampling methods based on detectability. Adaptive sampling. Spatial sampling. Mark and recapture methods. The jackknife, the bootstrap, and resampling plans. (Prerequisites: STAT 200 (Juneau STAT 373); STAT 401 recommended, or permission of instructor). Example text: Sampling by Thompson.
3 credits Data Analysis in Biology (2+3)
Biological applications of nonparametric statistics, including tests based on binomial and Poisson distributions, analysis of two-way and multiway contingency tables, and tests based on ranks; multivariate statistics, including principle component analysis ordination techniques, cluster analysis, and discriminate analysis; and time-series analyses. Introduction to the use of the computer, and use of statistical packages. Each student will analyze a data set appropriate to the student's research interests. (Prerequisites: STAT 300, 401 and either graduate standing in a biologically oriented field or permission of instructor). Example text: none.
* - These courses require approval which will be sought during fall 1995. PROPOSED COURSE SCHEDULE TO IMPLEMENT INTERDISCIPLINARY M.S. PROGRAM SEMESTER/YEAR ---- F95 S96 F96 S97 F97 S98 F98 S99 F99
STAT 200 200
STAT 200 200 200 200 200 200 200 200 200 200
STAT 200 200 200 200 200 200 200 200 200 200
STAT 200 200 200 200 200 200 200 200 200 200
STAT 401 401 401 401 401 401 401 401 401 401
STAT 300 300 300 300 300
STAT 402 402 402 402 402 402
STAT 461 461 461
STAT 602 602
STAT 605 AS DEMAND WARRANTS (taught as a Special Topics course during Spring 1995)
STAT 611 AS DEMAND WARRANTS (to be taught as a Special Topics course during Spring 1996) STAT 621 AS DEMAND WARRANTS (historically taught alternate years)
STAT 631 631 631 631
STAT 651 651 651 651 651
STAT 652 652 652 652
STAT 653 653 653 653
STAT 654 654 654 654
STAT 661 661 661
MATH 371 371 371 371
MATH 408 408 408 408
F95 S96 F96 S97 F97 S98 F98 S99 F99
AS DEMAND WARRANT courses would be offered for example when a faculty member from mathematics taught MATH 371, when our adjunct faculty member taught a course, when a non-statistics faculty member or lecturer taught a section of STAT 200, or when a statistics faculty member took on an addition section for one semester.