Independent and parallel visual processing of ensemble statistics: Evidence from dual tasks
An example
Greater or smaller than average?
Ensemble summary statistics
Independence
Correlational approach
Parallelism
Parallelism test
Parallelism test
Experiment 1
Procedure
Design
Data analysis
Individual correlations
Average errors
Conclusion
Experiment 2
Procedure
Design
Individual correlations
Average errors
Conclusions
Conclusions (2)
For details and even one more experiment please read: Khvostov V.A., Utochkin I. S. Independent and parallel visual processing
Thank you for being with me till the end of the first part
Confidence intervals in within-subject designs
It is all from this 4-pages paper
The problem
ANOVA results
Results of the experiment
The individual results of the 16 participants
The solution of the problem
Example of calculations
The individual results of the 16 participants after the individual differences were removed
The graph after the individual differences were removed
Example from real life
Example from real life
Hope you will use it
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Категория: ИнформатикаИнформатика

Independent and parallel visual processing of ensemble statistics: Evidence from dual tasks

1.

2. Independent and parallel visual processing of ensemble statistics: Evidence from dual tasks

3. An example

4. Greater or smaller than average?

5. Ensemble summary statistics

6. Independence

MEAN
NUMEROSITY
RANGE

7. Correlational approach

Different
sources of
noise
One source of
noise
No correlation
between errors in reports
of different statistics
Correlation
between errors in reports
of different statistics

8. Parallelism

MEAN
NUMEROSITY
REPORT
REPORT
VARIANCE
REPORT
MEAN
NUMEROSITY
REPORT
VARIANCE

9. Parallelism test

Single task
Observers should compute
only one statistics
Dual task
Observers should compute
both statistics

10. Parallelism test

No interference
Error in
single task
Error in
dual task
Interference
Error in
single task
Error in
dual task

11. Experiment 1

12. Procedure

13. Design

3 blocks
MEAN
NIMEROSITY
BOTH
6 “variables”

14. Data analysis

Error =
о
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