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Questions for Reviewers:

• What do you notice in the visualization?
  • your answer
• What questions do you have about the data?
  • your answer
• What relationships do you notice?
  • your answer
• What do you think is the main take-away from this visualization?
  • your answer
• Is there something you don’t understand in the graphic?
  • your answer

Any Additions Comments:

• your comments

Feedback
Questions for Reviewers:

What do you notice in the visualization?
    The large jump between going above the x axis and then it dropping downing into the negatives.  And the way that the shifts are any where from small to large.
What questions do you have about the data?
    What makes the difference between delay arrival time and why do the years really matter?
What relationships do you notice?
    The way that the orange dots seem to stay in the same base arrangement even with the large change in the minutes.
What do you think is the main take-away from this visualization?
    Just how much of a delay there are over the years for the different major airlines.
Is there something you don’t understand in the graphic?
Not really.

Any Additions Comments:

make the colors of the graph a little more differing because the pastel colors are to similar in saturation.

What do you notice in the visualization?

I first noticed how much easier it was to detect trends when the years flow automatically across. Not having to take my eyes off the data or trend pattern to click on different years gave a better appreciation for gaps in info. To go back and single out a year is also simple to do.

What questions do you have about the data?
How to keep raw data integrity in check - i.e.: one time meaning a plane pulls away from the gate, or actually takes off?

What relationships do you notice?

It appears to mostly remain consistently inconsistent.

What do you think is the main take-away from this visualization?

Very smart, easy to read way to interpret what would normally be a very cumbersome data set. Very good to market / prove on time capabilities to consumer, or investors.

Is there something you don’t understand in the graphic?

Per airport numbers were a little confusing, but that may be my system may not meet requirements.

Any Additions Comments:

Very exciting to check this out!

•What do you notice in the visualization?
When filtered by airline, the airline dots (info) disappears from graph and when airline re-clicked it does not reappear. If all airlines are clicked the graph goes blank and stays blank, have to refresh screen to bring back data.

Sometimes after picking a year or airport the visualization starts scrolling again when should stay paused?

•What questions do you have about the data?
None, really. It is presented clearly

•What relationships do you notice?
Southwest airlines started to take delays seriously in 2005 and has best showing in the list at most destinations in the following years,

•What do you think is the main take-away from this visualization?
Fly Southwest

•Is there something you don’t understand in the graphic?
It is difficult to tell which Airport is being represented in the graph because when you click the airport it stays highlighted even when the next airport is picked.
Maybe graph titles which change with selections picked to show what airport and year is being shown??

Any Additions Comments:
Very interesting!

Feedback
Questions for Reviewers:

What do you notice in the visualization?
    your answer   Delay times arriving flights
What questions do you have about the data?
    your answer  After clicking on some airlines and then trying to retrieve  them,it was not possible
What relationships do you notice?
    your answer  It appears Monday, Thursday & Friday have on average most delays
What do you think is the main take-away from this visualization?
    your answer Make plans to fly Tuesday, Wednesday or Sunday
Is there something you don’t understand in the graphic?
    your answer It is  pretty self explanatory

Any Additions Comments:
your comments