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Applied Statistical Analysis in Geography and Environment

Course Description: The course describes statistical analysis and its various applications in geography. It covers measurement methods, standards, and projections, as well as types and methods of data collection. It also addresses the most important analysis techniques for geographic data using applied statistical software including SPSS, Microsoft Excel, Stata, and R.
Credit hours: 3
Objectives of the course :

1- Understanding the scientific foundations on which statistical analyses are based.
2. Survey of Natural Resources; Statistical Methods and Utilization.
Developing the ability to choose appropriate statistical analyses for the research problems under study.
4. The ability to use computer programs to perform statistical analyses of geographical and environmental phenomena.
5. Understanding the concept of morphometric analysis of natural phenomena.
6- Identification of the most important petrographic analysis and geomorphological history techniques for sediment samples.
Enabling students to employ descriptive and inferential statistical methods in the analysis of geographical and environmental data, contributing to the interpretation of spatial phenomena, extracting relationships and patterns, and supporting evidence-based decision-making. This enhances scientific research capabilities and data-driven environmental planning.

Course outputs :

The student accurately identifies different statistical analyses for natural geographic phenomena.
It thoroughly recognizes statistical applications in natural fields.
Recognizes the most important statistical programs
Clearly explains the principles and concepts of statistical analysis.
Uses appropriate hardware and software to study a natural environmental problem
The student can match spatial data with field data when collecting statistical data.
Commitment to integrity and scientific research ethics in writing statistical reports
The student collaborates with peers to discuss an environmental problem and its solution.
The student collaborates with their peers in using environmental statistical software and devices.

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  • Last updated: 2026-04-29

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