Sample Selector

Sample Selector is a tool for creating and editing samples, or groups of data you compare across—they're not "samples" in the statistical sense, but more like filters.

By default, a single sample exists: "All Data". With the Sample Selector, you can create new samples to organize your data.

You can use samples to:

Compare across conditions
Narrow the scope of data analysis to a specific time range, set of students, problem category, or unit of a curriculum (for example)

A sample is composed of one or more filters, specific conditions that narrow down your sample.

Creating a sample

The general process for creating a sample is to:

Add a filter from the categories at the left to the composition area at the right
Modify the filter to select the subset of data you're interested in, saving it when done
View the sample preview table to see the effect of adding your filter, making sure you don't have an empty set (ie, a filter or combination of filters that exclude all transactions).
Name and describe the sample
Decide whether to share the sample with others who can view the dataset
Save the sample

The effect of multiple filters

DataShop interprets each filter after the first as an additional restriction on the data that is included in the sample. This is also known as a logical "AND". You can see the results of multiple filters in the sample preview as soon as all filters are "saved".

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Terms of Use

Effective January 16, 2012

By using the DataShop web application or web services, or by downloading data from DataShop, you agree to the following terms of use:

Data is for research purposes, not commercial purposes.
You will not make any attempts to de-anonymize the data.
DataShop makes no guarantees about the data in terms of quality or future availability.
You will not distribute data obtained from DataShop. If you are collaborating with others who require access to the data, they must establish accounts with DataShop and agree to these terms.
You agree to indemnify and hold harmless Carnegie Mellon University, the Pittsburgh Science of Learning Center (PSLC), and DataShop of and from any and all claims, demands, losses, causes of action, damage, lawsuits, judgments, including attorneys' fees and costs, arising out of or relating to your use and analysis of the data.
You will not attempt to modify or create a dataset with information that identifies students.
Data/files uploaded must be educational in nature for the purposes of research.
DataShop is not responsible for any content uploaded by its users.
You may only upload content that is not subject to any copyright, or content in which the author has given express authorization for distribution on the Web. Any copyrighted content distributed with the consent of a copyright owner should contain a phrase such as "Copyright, owned by [name of owner]; used by permission." If publishing an academic article, check with the publisher to see what kind of redistribution they allow. In many cases, the author of a work may only distribute a pre-print version of the article on the Web or in an open repository such as DataShop.
The DataShop team maintains the right to ban users or IP addresses at the team's discretion, for instance, if a user violates any of these terms.

Yes, I agree to these terms (required)


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