Geographers seek to describe and explain the patterns they see in both natural and human landscapes. They do so by collecting data on the phenomena, usually with a spatial focus. This is followed by application of a variety of data analysis methods, including visualization, descriptive statistics, inferential statistics (to make inferences and explain) and spatial analysis. Today’s software tools such as spreadsheets, Geographic Information Systems (GIS), and statistical analysis software greatly ease and enhance these efforts.
This course provides hands-on experience with the application of research methods used in geography and environmental studies. The course focuses on how data can be used to both explore new theory and to evaluate existing theories and hypotheses. Geographic and environmental examples will be used to illustrate the methods and concepts introduced throughout the course.
Topics will include research design, statistical models, descriptive and inferential statistical analysis, spatial analysis, and communication of research results. In the lab assignments, students will learn how to formulate research questions, design and perform data collection, and analyze and interpret data. Students will gain experience using analytical software, including R/R-Studio and other packages.
**Course Goals and Learning Outcomes ** The goal of this course is to develop an understanding of theory and application of analysis methods for geographical research. In completing this course, students will be able to:
- Understand how and why statistical methods are used in geographic research
- Critically evaluate academic research results
- Perform descriptive and inferential data analysis
- Learn how to use computer spreadsheets and statistical software for geographic problem solving