Jon Comer

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries andregions around the world. May not be used for degree credit with GLST 3723.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries and regions around the world. Same course as GEOG 3723.

An intermediate course in the application of statistical methods to spatial problems. Focuses on multivariate methods (e.g. multiple regression, factor and cluster analysis) and their use in geographic settings and with spatial datasets. Includes introductory spatial regression, methods for detecting spatial clusters (spatial autocorrelation), and the importance of exploratory spatial data analysis (ESDA) in geographic research. Course previously offered as GEOG 5313.Prerequisite(s): One course in statistics.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

Offered for variable credit, 1-3 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of instructor.

An introductory course in the application of basic statistical methods to spatial problems, including descriptive statistics, probability distributions, point and interval estimation, hypothesis testing, correlation, and simple linear regression. Emphasizes the challenges of working with spatial datasets and choosing appropriate methods of analysis, as well as explicitly spatial methods such as spatial sampling, point and area pattern analysis, and spatial autocorrelation. Provides a foundation for further study in geospatial technologies.Prerequisite(s): STAT 2013 or STAT 2023 or STAT 2053 or STAT 4013 or STAT 4053.

An intermediate course in the application of statistical methods to spatial problems. Focuses on multivariate methods (e.g. multiple regression, factor and cluster analysis) and their use in geographic settings and with spatial datasets. Includes introductory spatial regression, methods for detecting spatial clusters (spatial autocorrelation), and the importance of exploratory spatial data analysis (ESDA) in geographic research. Course previously offered as GEOG 5313.Prerequisite(s): One course in statistics.

An introductory course in the application of basic statistical methods to spatial problems, including descriptive statistics, probability distributions, point and interval estimation, hypothesis testing, correlation, and simple linear regression. Emphasizes the challenges of working with spatial datasets and choosing appropriate methods of analysis, as well as explicitly spatial methods such as spatial sampling, point and area pattern analysis, and spatial autocorrelation. Provides a foundation for further study in geospatial technologies.Prerequisite(s): STAT 2013 or STAT 2023 or STAT 2053 or STAT 4013 or STAT 4053.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

An intermediate course in the application of statistical methods to spatial problems. Focuses on multivariate methods (e.g. multiple regression, factor and cluster analysis) and their use in geographic settings and with spatial datasets. Includes introductory spatial regression, methods for detecting spatial clusters (spatial autocorrelation), and the importance of exploratory spatial data analysis (ESDA) in geographic research. Course previously offered as GEOG 5313.Prerequisite(s): One course in statistics.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

Offered for variable credit, 1-3 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of instructor.

An introductory course in the application of basic statistical methods to spatial problems, including descriptive statistics, probability distributions, point and interval estimation, hypothesis testing, correlation, and simple linear regression. Emphasizes the challenges of working with spatial datasets and choosing appropriate methods of analysis, as well as explicitly spatial methods such as spatial sampling, point and area pattern analysis, and spatial autocorrelation. Provides a foundation for further study in geospatial technologies.Prerequisite(s): STAT 2013 or STAT 2023 or STAT 2053 or STAT 4013 or STAT 4053.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries andregions around the world. May not be used for degree credit with GLST 3723.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries and regions around the world. Same course as GEOG 3723.

A non-quantitative introduction to weather. Physical elements that cause and influence the atmosphere over the short term. Energy, moisture, and storms. Interpretation of weather maps and satellite imagery.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries andregions around the world. May not be used for degree credit with GLST 3723.

This course examines the cultural, economic, and natural diversity of Europe in relation to globalization, climate change, and popular culture. Basic geographic concepts such as migration, region, and culture will be linked to European current events. Students will learn to properly utilize online sources to understand current European issues and their relationship to other countries and regions around the world. Same course as GEOG 3723.

Offered for variable credit, 1-3 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of instructor.

An introductory course in the application of basic statistical methods to spatial problems, including descriptive statistics, probability distributions, point and interval estimation, hypothesis testing, correlation, and simple linear regression. Emphasizes the challenges of working with spatial datasets and choosing appropriate methods of analysis, as well as explicitly spatial methods such as spatial sampling, point and area pattern analysis, and spatial autocorrelation. Provides a foundation for further study in geospatial technologies.Prerequisite(s): STAT 2013 or STAT 2023 or STAT 2053 or STAT 4013 or STAT 4053.

Offered for variable credit, 1-12 credit hours, maximum of 30 credit hours.Prerequisite(s): Admission to candidacy and consent of major professor.