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How to Run Data SGP Analyses

  • How to Run Data SGP Analyses
16/02/2025
By mnblackchamber In Gambling Blog

How to Run Data SGP Analyses

Data SGP is an educational data analytics package which uses state test scores to measure student progress against academic peers in the same grade. Built using open-source R software and available for Windows, OSX and Linux operating systems; operating it may require some familiarity with R prior to use but running SGP analyses is typically straightforward.

SGP analyses begin by prepping data. There are two primary ways of prepping data: via file or manually entering it into an SGP analysis tool. Either way, data must be properly formatted and scaled prior to being utilized in SGP analyses.

There are various functions within the SGP package which can be used to prepare SGP data for analysis, with sgpData being one of the more commonly utilized. This function creates an exemplar data set which can then be utilized with lower level studentGrowthPercentiles and studentGrowthProjections functions; additionally it can also be combined with higher-level wrapper functions that simplify analysis processes.

To use SGP analyses, users need access to both the SGP package and a computer connected via network. As it’s open source and easily downloaded onto computers, this package should be no problem at all for most major operating systems and platforms. Although running analyses locally is certainly feasible, we strongly advise taking advantage of server environments like Amazon Web Services (AWS).

To use SGP analyses effectively, the user needs an SGP account, an AWS instance and the necessary credentials. SGP accounts are free and can be created through either the AWS dashboard or following a link provided in SGP documentation.

Once credentials have been established, users can upload and analyze their data. Data may be uploaded in multiple formats; we suggest using the sgpData function, as it provides several useful statistics for assessing data quality as well as visualization tools that help uncover trends within it.

Users typically perform SGP analyses on multiple years of data at once. To facilitate this analysis, the SGP package allows up to four years’ worth of assessment years to be analyzed simultaneously in one pass. In order to do this effectively, an aggregation method must first be chosen which groups them together before all selected assessment data will be processed into individual SGP results for each student.

Once a student’s SGP results have been generated, they can be displayed in various ways. A common way is on a graph which depicts current and past performance relative to academic peers; this graph can also be sorted based on criteria like average score or percentile rank.

SGP results are reported on a 1-99 scale, where 99 represents maximum relative growth. A low SGP result signifies little or no educational advancement for a student; conversely, high results signify above-expected performance at their grade level.

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