Log in to start analyzing data.

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:

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:

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".

Help

Baker - Building Generalizable Fine-grained Detectors (private) (terms of use)

Datasets Terms of Use

Project Terms of Use

Effective May 21, 2013

Carnegie Learning Private Dataset Terms of Use

Access to Carnegie Learning's datasets is conditional upon agreement to the following terms:

  • You agree to use these data for academic research purposes only. You agree that these data and any analyses of these data will not be used in development or marketing of commercial products.
  • You will acknowledge Carnegie Learning in any publication resulting from this research and notify Carnegie Learning (researchpartner@carnegielearning.com) of any publications resulting from this research. In addition, academic papers and similar results of research should make references according to the following:
  • Upon completion of the research project, you will notify Carnegie Learning (researchpartner@carnegielearning.com)
  • You will not attempt to determine the identity of any individuals (including both teachers and students) or schools represented in the dataset(s).
  • Any published results must not include the identity of any individuals (either students or teachers), schools or school districts, whether such identities are determined from the data itself or from some other source.
  • Published data must be in summary or statistical form. You may not disclose or report on any individual student data, even if such data is anonymous.
  • You agree not to use these data to attempt to discover, implement or reverse engineer the Cognitive Tutor®, MATHia®, Fast ForWord or other software or any functions of such software.
  • You are the only person who will access these data. If you are collaborating with others who require access to these data, they must independently agree to these terms.
  • If you make copies of the data, you must destroy these copies at the completion of the research project or at the request of Carnegie Learning.
  • If your access to the dataset(s) includes web service access, you will take no actions jeopardizing the availability and accessibility of the dataset(s).
  • To the extent authorized under the laws of your state, you agree to indemnify and hold harmless Carnegie Learning, its parent, affiliates, subsidiaries and their respective directors, officers, employees and agents 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 Carnegie Learning dataset(s) or your violation of this Agreement.
  • Carnegie Learning reserves the right, in its sole discretion, to change these terms of use or discontinue your access to the dataset(s) at any time, without notice.

DataShop Terms of Use

The DataShop terms of use also apply.