Data SGP

Located on 160 acres of cattle pasture and wheat fields southeast of Lamont, the SGP site has a large number of continuously instrumented facilities and satellite sensors to collect a variety of atmospheric data. The site provides data and information for scientists to use in a range of applications from single observation analyses, multi-observation process studies, to assimilation into Earth system models.

SGP members have assembled or generated multi-proxy sedimentary geochemical data (iron, carbon, sulfur, and major and trace metal isotopes) from shale intervals across the Neoproterozoic through Paleozoic time slices. This data has been used to address a range of scientific questions and is being integrated into larger community databases such as Genbank, EarthChem, and others.

The SGP Project is funded by the National Science Foundation and consists of an international consortium of universities and research laboratories. The research activities are conducted by Working Groups, each led by a member institution. Working Groups are charged with addressing a particular scientific question of interest. Although the outputs of each Working Group will ultimately be integrated into these larger community databases, the fundamental purpose of the SGP Project is to address specific research questions of immediate relevance to researchers.

While there is some overlap in the research goals of the Working Groups, the overall scope of the SGP project has been defined as a large-scale, long term effort to assemble or generate multi-proxy sedimentary geochemical data covering all of the Earth’s time domains. This data will be used to understand the role of these variables in past and future climate change and provide a basis for future policy and resource planning.

Data sgp is an online system that makes it easy to access and analyze growth percentiles and student growth projections. These tools compare a student’s progress to that of their academic peers nationwide. These “academic peers” are students in the same grade and assessment subject who have a similar score history on Star assessments. They are not matched by demographics, or by any other factors that might bias their comparisons.

SGP analyses are typically conducted in 6 steps: preparing the data, creating a list of student records, generating the list of student aggregates, calculating student growth and achievement percentiles, and displaying the results. These 6 steps are repeated for each window of data and each content area within the data. SGP Package wrapper functions such as abcSGP and prepareSGP simplify this process to a single function call, making it much easier to run operational SGP analyses.

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