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".

Read more about the Sample Selector

Discourse Info

This page provides an overview for the current discourse. It may answer questions such as:

• When were these data collected?
• What's the scope of the discourse?
• What types of data sources are present in the discourse?
• What is the contribution type make-up of the discourse?

Discourse statistics at a glance

You can gauge the size of the discourse by looking at the number of users, data sources and contributions.

Read more about Discourse Info