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EESC 7771G Geostatistics
30 hours lecture; 30 hours lab; 3 credits
This course will introduce students to the fundamentals of data exploration and applied inferential statistics within the context of datasets relevant for earth and environmental sciences. Major topics include statistical description of data; collection of data; probability; hypothesis testing; variance; correlation; spatial analysis; multivariate analysis; sampling considerations; graphical display of data; common distribution models; and regression. Course material related to statistical concepts will be complemented with hands-on training and data analysis using statistical programming software such as R, SPSS, Python, Matlab, or Excel.
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The City University reserves the right, because of changing conditions,
to make modifications of any nature in academic programs and requirements
of the university and its constituent colleges without advanced notice.
Students are advised to consult regularly with college and department counselors
concerning their programs of study.
Access the college's current and recent course bulletins.
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