STAT F200X      Elementary Statistics      (m)
3 Credits

Introduction to concepts and applications of elementary statistical methods. Topics include sampling and data analysis, descriptive statistics, elementary probability, probability and sampling distributions, confidence intervals, hypothesis testing, correlation, and simple linear regression.

Prerequisites: Appropriate placement score; or a grade of B or better in DEVM F105 or DEVM F105N or in all three of DEVM F105G and DEVM F105H and DEVM F105J; or grade of C- or better in a higher-level math course.

Attributes: UAF GER Mathematics Req

Lecture + Lab + Other: 3 + 0 + 0

STAT F300      Statistics
3 Credits

Offered Spring; Fall Odd-numbered Years

A calculus-based course emphasizing applications. Topics include probability, joint and conditional probability, expectation and variance, parameter estimation (method of moments and maximum likelihood), one and two sample hypothesis tests, simple linear regression and one-way analysis of variance. A student may not use STAT F200X and STAT F300 to meet the requirement of a year's sequence course in statistics.

Prerequisites: MATH F230X or MATH F251X or placement.

Lecture + Lab + Other: 3 + 0 + 0

STAT F401      Regression and Analysis of Variance
4 Credits

Offered As Demand Warrants

Thorough study of multiple regression including multiple and partial correlation, the extra sum of squares principle, indicator variables, polynomial models, model selection techniques and assessment of underlying assumptions. Analysis of variance and covariance for multifactor studies in completely random and randomized complete block designs, multiple comparisons and orthogonal contrasts. Matrix concepts for linear models are taught as needed.

Prerequisites: STAT F200X or STAT F300.

Lecture + Lab + Other: 3 + 3 + 0

STAT F402      Scientific Sampling
3 Credits

Offered Fall

Sampling methods, including simple random, stratified and systematic and one- and two-stage cluster sampling; estimation procedures, including ratio and regression methods; special area and point sampling procedures; optimum allocation. Adaptive and probability sampling; bootstrapping and basic mark-and-recapture.

Prerequisites: STAT F200X or STAT F300.

Lecture + Lab + Other: 3 + 0 + 0

STAT F454      Statistical Consulting Seminar
1 Credit

Offered Spring

Introduction to statistical consulting and data analysis. Emphasis on interaction with researchers and identification of scientific and statistical issues relevant to the research problem. Includes regular class meetings as well as supervised meetings with researchers. Designed to combine mathematical statistics with applications from a variety of fields. Students from any field of study with strong quantitative skills are encouraged to enroll. May be repeated for a total of three credits.

Prerequisites: STAT F200X or STAT F300; STAT F401; and MATH F408.

Stacked with STAT F654.

Lecture + Lab + Other: 1 + 0 + 0

STAT F461      Applied Multivariate Statistics
3 Credits

Offered Spring Even-numbered Years

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.

Prerequisites: STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F602      Experimental Design
3 Credits

Offered Fall Even-numbered Years

Constructing and analyzing designs for experimental investigations; completely randomized, randomized block and Latin-square designs, split-plot design, incomplete block design, confounded factorial designs, nested designs, treatment of missing data, comparison of designs.

Prerequisites: STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F605      Spatial Statistics
3 Credits

Offered Spring Even-numbered Years

Stochastic processes and variograms. 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 F401; MATH F251X; MATH F252X; MATH F253X.

Lecture + Lab + Other: 3 + 0 + 0

STAT F611      Time Series
3 Credits

Offered Spring Odd-numbered Years

An applied course in time series and repeated measure analysis. Autoregression and moving average models. Estimation of parameters and tests. Prediction. Spectral analysis. Analysis of repeated measures data.

Prerequisites: STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F621      Distribution-free Statistics
3 Credits

Offered Fall Odd-numbered Years

Bootstapping, simulation, randomization tests and jackknifing. Classical distribution-free tests and confidence intervals including the Wilcoxen test, Kolmororov-Smirnov, Friedman test, Spearman's and Kendall's correlations, Kruskal-Wallis test, Sign tests and Fisher's exact tests. The practice of non-parametric regression including methods such as generalized additive models, polynomial and spline regression, penalized splines, regression trees, neural nets, gradient boosting, kernal regression methods, isotonic regression and kriging. Robust and resistant estimation methods. Non-parametric density estimation. Survival analysis including Kaplan-Meier and proportional hazards regression.

Prerequisites: STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F631      Categorical Data Analysis
3 Credits

Offered Fall Odd-numbered Years

Statistical methods designed for count and categorical data. Contingency tables. Logistic and related models. Log-linear models. Repeated categorical responses. Survival data.

Prerequisites: STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F641      Bayesian Statistics
3 Credits

Offered Fall Even-numbered Years

Bayes' Rule, Bayesian models for universal data, prior selection (conjugate and non-conjugate, noninformative and objective priors). Single parameter and multiparameter models. Hierarchical models, general linear model and mixed models. Study of posterior simulation techniques including Markov chain Monte Carlo. Model validation and model selection. Emphasis on applications, using modern statistical software packages.

Prerequisites: MATH F252X; MATH F371, MATH F401, MATH F404, MATH F405, MATH F408 or STAT F651.

Lecture + Lab + Other: 3 + 0 + 0

STAT F642      Bayesian Decision Theory for Resource Management
4 Credits

Offered Spring Even-numbered Years

Application of decision theory to problems in natural resources management. Students will learn to perform Bayesian calculations and uncomplicated decision analysis themselves.

Prerequisites: FISH F621 or FISH F630.

Cross-listed with FISH F642.

Lecture + Lab + Other: 2 + 2 + 0

STAT F651      Statistical Theory I
3 Credits

Offered Fall

Probability and distribution of random variables. Conditional probability and stochastic independence. Distributions of functions of random variables. Expected values. Limiting distributions. Distributions derived from the normal distribution. Designed to combine mathematical statistics with applications from a variety of fields. Students from any field of study with strong quantitative skills are encouraged to enroll.

Prerequisites: MATH F253X; MATH F314; previous statistics course.

Lecture + Lab + Other: 3 + 0 + 0

STAT F652      Statistical Theory II
4 Credits

Offered Spring Odd-numbered Years

Estimation of parameters. Efficiency and sufficiency. Hypothesis testing. The Neyman-Pearson paradigm and likelihood ratio tests. Data summaries. Bootstrap. Comparison of two samples. Linear least squares. Analysis of categorical data. Bayesian inference. Designed to combine mathematical statistics with applications from a variety of fields. Students from any field of study with strong quantitative skills are encouraged to enroll.

Prerequisites: STAT F651.

Lecture + Lab + Other: 4 + 0 + 0

STAT F653      Statistical Theory III: Linear Models
3 Credits

Offered Spring Even-numbered Years

Best linear unbiased estimation in the general linear model, 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 and generalized linear models. Designed to combine mathematical statistics with applications from a variety of fields. STAT F401 or equivalent course in applied linear regression modeling is strongly recommended.Student must take 651 or all the other courses listed.

Prerequisites: STAT F651 or MATH F371; MATH F253X; MATH F314.

Lecture + Lab + Other: 3 + 0 + 0

STAT F654      Statistical Consulting Seminar
1 Credit

Offered Spring

Introduction to statistical consulting and data analysis. Emphasis on interaction with researchers and identification of scientific and statistical issues relevant to the research problem. Includes regular class meetings as well as supervised meetings with researchers. Designed to combine mathematical statistics with applications from a variety of fields. Students from any field of study with strong quantitative skills are encouraged to enroll. May be repeated for a total of three credits.

Prerequisites: STAT F200X or STAT F300; STAT F401; and MATH F408.

Stacked with STAT F454.

Lecture + Lab + Other: 1 + 0 + 0

STAT F661      Sampling Theory
3 Credits

Offered As Demand Warrants

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 F200X; STAT F401.

Lecture + Lab + Other: 3 + 0 + 0

STAT F692      Seminar
1-6 Credits

Lecture + Lab + Other: 0 + 0 + 0

STAT F692A      Seminar
1-6 Credits

Lecture + Lab + Other: 0 + 0 + 0

STAT F692P      Seminar
1-6 Credits

Lecture + Lab + Other: 0 + 0 + 0

STAT F698      Non-thesis Research/Project
1-6 Credits

Lecture + Lab + Other: 0 + 0 + 0