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## CLA-ASR_benchmark.md

      
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              Created
              April 2, 2018 01:26
            
          
    ASR Benchmark Individual Contributor License Agreement

In order to clarify the intellectual property license granted with Contributions from any person or entity, Franck Dernoncourt and must have a Contributor License Agreement ("CLA") on file that has been signed by each Contributor, indicating agreement to the license terms below. This license is for your protection as a Contributor as well as the protection of Franck Dernoncourt; it does not change your rights to use your own Contributions for any other purpose.
You accept and agree to the following terms and conditions for Your present and future Contributions submitted to Franck Dernoncourt. Except for the license granted herein to Franck Dernoncourt and recipients of software distributed by Franck Dernoncourt, You reserve all right, title, and interest in and to Your Contributions.

Definitions.

"You" (or "Your") shall mean the copyright owner or legal entity authorized by the copyright owner that is making this Agreement with Franck Dernonc

  
## mapping_hadm_id_waveform_id.csv

          
            SUBJECT_ID
             HADM_ID
             waveform ID

            
              20
              3039
              3544749

            
              33
              12597
              3713820

            
              33
              12597
              3737936

            
              52
              11109
              3238451

            
              52
              11109
              3533390

            
              79
              12220
              3842928

            
              79
              12220
              3887555

            
              123
              17817
              3485814

            
              123
              17817
              3348632

## bgw03.sql
-- Q1: Aggregate the data to develop detectors at the student-level. Which student has the highest percentage of gaming? (Hint: One way to do this is to create a dummy variable for each observation, 1 if gaming, 0 if not gaming, and then make a pivot table)
-- A: Open bigdata-edu-Data-Sets-Data-Subset-Pardos-et-al-2013-observations
-- Week 3B.csv with Excel, sort by double-anon-userID and you'll see that the
-- student 39769525 has just one row, wwhich is flagged as GAMING, which
-- means this student has a 100% of gaming. So 39769525 is the answer.

-- Q2: Aggregate the data to develop detectors at the student-level. How many students were never bored in any observation?
SELECT
    COUNT(*)
FROM
SUBJECT_ID	HADM_ID	waveform ID
20	3039	3544749
33	12597	3713820
33	12597	3737936
52	11109	3238451
52	11109	3533390
79	12220	3842928
79	12220	3887555
123	17817	3485814
123	17817	3348632
	-- Q1: Aggregate the data to develop detectors at the student-level. Which student has the highest percentage of gaming? (Hint: One way to do this is to create a dummy variable for each observation, 1 if gaming, 0 if not gaming, and then make a pivot table)
	-- A: Open bigdata-edu-Data-Sets-Data-Subset-Pardos-et-al-2013-observations
	-- Week 3B.csv with Excel, sort by double-anon-userID and you'll see that the
	-- student 39769525 has just one row, wwhich is flagged as GAMING, which
	-- means this student has a 100% of gaming. So 39769525 is the answer.

	-- Q2: Aggregate the data to develop detectors at the student-level. How many students were never bored in any observation?
	SELECT
	COUNT(*)
	FROM