In retrospect, my forecast that the median response to the first question would be as low as 10% was too ambitious. That would have been surprisingly low for a median.
I think my other forecasts were good. My 18% mean on Q1 was so low only because my median was low. Interestingly my own answer for Q1 was 20%, which was exactly the median response. I forget why I thought the mean and median answer would be lower than mine.
The Elicit predictions:
Actual: mean: (~0.3, ~0.4), median: (0.2, 0.3)
elifland: mean: (.23, .33), median: (.15, .25)
WilliamKiely: mean: (0.18, 0.45), median: (0.1, 0.3)
Ben Pace: mean: (0.15, 0.17), median: (.15, .17)
bsokolowsky: mean: (0.69, .40), median: (.64, .37)
MichaelA: mean: (0.14, N/A), median: (0.06, N/A)
SamClarke: mean (N/A, N/A), median: (0.05, 0.05)
Scoring Elicit predictions by margin of error, we get:
elifland: mean: (-.07, -.07), median: (-.05, -.05) - Sum of abs.value(errors): 0.24
WilliamKiely: mean: (-0.12, 0.05), median: (-.1, 0) - Sum of errors: 0.27
Ben Pace: mean: (-0.15, 0.23), median: (-.1, 15) - Sum of errors: 0.63
bsokolowsky: mean: (0.39, 0), median: (.44, .07) - Sum of errors: 0.90
MichaelA: mean: (-0.16, N/A), median: (-.24, N/A) - Sum of two errors: 0.40 (only Q1)
SamClarke: mean (N/A, N/A), median: (-.15,-0.25) - Sum of two errors: 0.40 (medians only)
In retrospect, my forecast that the median response to the first question would be as low as 10% was too ambitious. That would have been surprisingly low for a median.
I think my other forecasts were good. My 18% mean on Q1 was so low only because my median was low. Interestingly my own answer for Q1 was 20%, which was exactly the median response. I forget why I thought the mean and median answer would be lower than mine.