## ← Overplotting and Domain Knowledge - Data Analysis with R

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Showing Revision 3 created 05/24/2016 by Udacity Robot.

1. In the last exercise, we used alpha and jitter to reduce
2. over plotting, but it turns out that there's more that we can
3. do. Let's hear from Mora about how she used her domain
4. knowledge and a transformation to make an adjustment to her scatter plot.
5. >> The next thing that I did, was
6. to take again, the perceived audience size, and their
7. actual audience size, but this time I transformed
8. the axes. So this time, it's as a percentage
9. of their friend count. Some people in this study had
12. size as a percentage of the possible audience. All of
13. the people in the study had shared their post with
14. friends only privacy, so you'd expect that it would be
15. bounded by their friend count. So, what we found when
16. we plotted it this way was that all of the points
17. are below this line of perfect accuracy, this diagonal line, really
19. plot, we actually ran two different surveys. We ran one survey
20. where we asked people in a single post, how many people
21. do you think saw, saw your post? But we also asked
22. a different set of people, in general, how many people do
23. you think see the content that you share on Facebook? So
24. that's what this plot is showing. This is the in general
25. question, and their guesses are a little bit
26. higher. But still, people typically think people that maybe
27. 10% of their friends see their content when in
28. reality it's more like 40% or 50%, even 60%
29. of their friends will see their content in
30. a given month. So that's what this plot is
31. showing, is the percentage of friends who actually saw
32. their content in the last month, again, they're underestimating.