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

External Tools

Free tools submitted by developers in the educational data mining and intelligent tutoring systems communities. Please be aware that these files have been provided by users of the site; we cannot vouch for their accuracy or authenticity. To add your own tools, please log in.

Name Language Contributor Downloads Updated
Graphit 1.2 This R code will draw attractive graphs of correctness learning curves. Please see the instructions in the file and example calls on a public dataset: https://datashop.memphis.edu/DatasetInfo?datasetId=1465 . Currently the code graphs in black and white, with 1 SE error bars by default. The R file creates the html file, which requires the js file in the same folder. R Philip Pavlik 7 downloads 2016-10-21
SEMILAR - The Semantic Similarity Toolkit SEMILAR is the most widely used semantic similarity toolkit downloaded more than 4,000 times from 121 different countries and 49 U.S. states. In education, it has been successfully used for assessing open ended student responses that can vary in size from a word to a sentence to a paragraph or longer. target language is English, available as both a standalone applications and Java library Vasile Rus 0 downloads 2016-06-06
Wavelet based artifact removal from EEG data This MATLAB code can clean ocular artifacts (OA) from raw EEG data. The algorithm uses Wavelet Technique to decompose the raw signals, identify artifactual components, and reconstructs artifact-free EEG data. Matlab Bashir Morshed 2 downloads 2016-05-31
Version 9.3.4 March 2, 2017