Calibration Lecture PowerPoint PPT Presentation

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Title: Calibration Lecture


1
  • The aim of this presentation is to explain how to
    use the confidence response scale so that your
    confidence responses show good calibration.

2
Calibration Graph
  • In this slideshow, you will see graphs like the
    one to the right.
  • This graph represents calibration, or the
    correspondence between each confidence response
    category you use and the percentage of time you
    were correct about which item was more expensive.

3
  • The x-axis of the graph gives the confidence
    response categories that you chose among.
  • The y-axis of the graph gives the percentage of
    time you were correct about which item was more
    expensive.

4
  • For instance, we would count the number of times
    you said 50, 60, etc confident (doing this
    separately for each confidence response category).
  • Then, we compute the percentage of times the item
    you chose was more expensive for that particular
    confidence response category.

5
  • Lets say you said 100 chance 10 times
  • and the item you chose as more expensive is more
    expensive 8 of those times (80)
  • That would be demonstrated by the blue dot.

6
  • Now lets look at a perfectly calibrated
    participant
  • Out of all the times they said 50, the item they
    chose was more expensive 50 of the time
  • Out of all the times they said 60, the item they
    chose was more expensive 60 of the time
  • Etc.
  • Note that to be perfectly calibrated, you dont
    have to be correct all the time. Instead, your
    confidence responses should match the proportion
    of time your chosen item is more expensive.

7
  • Now lets look at a participant with poor
    calibration.
  • Many of the points are far from the line.
  • Out of all the times they said they were 90
    confident that they chose the more expensive
    item, their chosen item was more expensive only
    60 of the time.
  • Out of all the times they said they were 100
    confident, they were correct only 70 of the
    time.

8
  • And lets see an example with even worse
    calibration.
  • Here, every one of their dots is far from the
    line of perfect calibration.

9
  • To review, you want your points (the blue dots)
    to be as close to the line as possible.
  • Note it is very difficult to have your points
    fall exactly on the line. Just give your best
    estimates, and try to get as close as you can.
    The graph on the left, for example, would
    indicate good calibration.
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