STATISTICAL METHODS FOR SPATIAL DATA

STAT 575

Course Description

Detecting, quantifying, and modeling spatial patterns and structure in data. Variograms and covariance functions, linear predictions with uncertainty qualification, and conditional simulations. Spectral domain models and spectral densities. Spatial point processes. Contemporary applications and Gaussian process model fitting at scale.

Prerequisties

(STAT 333 or STAT 340 ) and (MATH 320 , MATH 340 , MATH 341 , or MATH 375 ), graduate/professional standing, or declared in Statistics VISP

Satisfies

This course does not satisfy any prerequisites.

Credits

Offered

Fall

Grade Point Average

3.31

-0.08% from Historical

Completion Rate

96.3%

-2.38% from Historical

A Rate

51.85%

3.7% from Historical

Class Size

9.46% from Historical

2025 Fall Grade Distribution

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

Similar Courses

STATISTICAL METHODS FOR DATA SCIENCE

STAT 613

Provides a thorough grounding in modern statistical methods. Introduces statistical techniques and methods of data analysis, including data description, linear regression models, diagnostic tools, prediction and model selection, and experimental design.

INTRODUCTION TO MACHINE LEARNING AND STATISTICAL PATTERN CLASSIFICATION

STAT 451

Pattern classification, regression analysis, clustering, and dimensionality reduction. For each category, covers fundamental algorithms and selections of contemporary, current state-of-the-art algorithms. Focus on evaluation of machine learning models using statistical methods. Statistical pattern classification approaches, including maximum likelihood estimation and Bayesian decision theory, algorithmic and nonparametric approaches. Practical use of machine learning algorithms using open source libraries from the Python programming ecosystem.

GIS AND SPATIAL ANALYSIS

GEOG 579

Principles and algorithms for spatial analysis in geographic imformation systems. A theoretical and practical examination of analytical methods used in GIS, including point, line and polygon processing, interpolation, smoothing, spatial overlay and query, network analysis, terrain analysis, and classification.

ADVANCED QUANTITATIVE METHODS

GEOG 560

Selected topics in the analysis of spatial distributions with emphasis on multivariate techniques.

STATISTICAL METHODS II

STAT 602

Provides a thorough grounding in modern statistical methods. The specific learning outcomes for the course are to understand data collection in context (how/why data were collected, key questions under study); explore data by effective graphical and numerical summaries; understand probability concepts and models as tools for studying random phenomena and for statistical inference; analyze data using appropriate, modern statistical models, methods, and software; understand the statistical concepts underlying methods; develop the ability to interpret results and critically evaluate the methods used; communicate data analysis and key findings in context.