Table of Contents

Data Structures Fall 2018 Status

Data and visualizations generated from class activity.

This information is provided to give you a better perspective on how the class as a whole is trending.

Numeric Stats on Deliverables

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DATA      dsi0 ael0 sln0 sln1 sll0 sll1  got+bns/totl tlly prjct+prtcp+jrnal=results ( grade )
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 lowscore:  69   66    0   50    0    0 .............  12% ......................... ( 47.091)
 avgscore:  91   93   88   88   84   74 .............  89% ......................... ( 49.801)
   median: 100  100  100   92   94   97 .............  98% ......................... ( 97.703)
  hiscore: 100  100  100  100  100  100 ............. 107% ......................... (106.229)
     mode: 100  100  100   95   98  100 
    range:  31   34  100   50  100  100 
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 # passed:  11   11   10   10   10    8 .............   10 ......................... 10 ( 90%)
  # of As:   7    9    9    5    6    7 .............    8 .........................  7 ( 63%)
  # of Bs:   2    1    0    5    3    1 .............    1 .........................  2 ( 18%)
  # of Cs:   2    1    1    0    1    0 .............    1 .........................  1 (  9%)
  # of Ds:   0    0    0    0    0    0 .............    0 .........................  0 (  0%)
  # of Fs:   0    0    1    1    1    3 .............    1 .........................  1 (  9%)
 # submit:  15   16   13   16   10   11 
  # early:  11    4    2    7    4    5 
  # onday:   8   12   12    7    6    5 
   # late:   1    2    1    1    1    1 
# missing:   1    1    4    1    5    4 
 % passed: 100% 100%  90%  90%  90%  72%
  % of As:  63%  81%  81%  45%  54%  63%
  % of Bs:  18%   9%   0%  45%  27%   9%
  % of Cs:  18%   9%   9%   0%   9%   0%
  % of Ds:   0%   0%   0%   0%   0%   0%
  % of Fs:   0%   0%   9%   9%   9%  27%
 % submit: 136% 145% 118% 145%  90% 100%
  % early: 100%  36%  18%  63%  36%  45%
  % onday:  72% 109% 109%  63%  54%  45%
   % late:   9%  18%   9%   9%   9%   9%
% missing:   9%   9%  36%   9%  45%  36%
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Class Project Progress

Of the various all-class metrics we can analyze:

We can visualize the results to gain a big picture view. The more the data stays within a certain range, the less interesting the graphs will appear. In such cases, boring graphs indicate the class as a whole is staying relatively the same with respect to that metric (dips would tend to indicate problems, rises would tend to indicate improvements).

Project Metrics

Project Metrics graph

Class Ranking

Project Ranking graph