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".
A project is primarily a group of related datasets. Each project has a principal
investigator (PI) and potentially a data provider, as well as one or more project
admins. If you are a project admin for this project, you can edit its metadata. The
difference between PI and project admin is described here.
Access to datasets is granted by project. To gain access to a private project, click
the Request Access button and provide a brief reason why you would like
access. The status of your request will be shown on the Access Requests page.
