topic02b_handouts - MullerLyer: Method of Adjustment...

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Unformatted text preview: MullerLyer: Method of Adjustment Muller-Lyer: Method of Adjustment 150 140 130 Line Length Ascending trials 120 110 100 90 0 1 2 3 4 5 6 7 8 9 10 11 Trial Descending trials Mean reference line length MullerLyer: Method of Limits Muller-Lyer: Method of Limits 150 140 130 Line Length Ascending trials 120 110 100 90 0 1 2 3 4 5 6 7 8 9 10 11 Trial Descending trials Mean reference line length MullerLyer: Method of Constants Muller-Lyer: Method of Constants 1.00 0.80 % Longer 0.60 0.40 0.20 0.00 100 110 120 130 140 150 Test Line Length Introducing Signal Detection Theory Psychological Evidence Independent Variable Dependent Variable x f(x) ? ? ? DV Perhaps We Need a New Threshold And We Get a Second Function! " Yes" if > c g( ) = " No" if c x DV f ( x) g( ) Still That Problem of Randomness Normal (Gaussian) distribution Signal Detection Theory and Detection Detect the presence of some external energy x f(x) f ( | s + n) c Hit Miss The Other State of the World f ( | n) Correct rejection c False alarm Another Look Yet Another Look Working With Data: Estimating Hit and False Alarm Rates State Response Of the World Present Absent Signal present (s+n) f1 f2 Signal absent (n) f1 Hit rate (HR) = f1 + f 2 f3 f4 f3 False alarm rate (FA) = f3 + f 4 Example Data Two Aspects of Performance x DV f ( x) g( ) Separate Pieces c Estimating Probabilities from Data c Quantifying Sensitivity d' = z ( HR ) - z ( FA ) d' = 1.036 - ( - 1.282 ) = 2.318 z(.10) = 1.282 HR = .85 c z(.85) = 1.036 c FA = .10 Interpreting d' Quantifying Bias 1 c = - [ z ( HR ) + z ( FA ) ] 2 Example 1: Detecting a tone R S Example 2: detecting a bad transmission R S ...
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This note was uploaded on 05/26/2008 for the course PSYCH 253 taught by Professor Wenger,michaeljasippel,laurenmic during the Fall '07 term at Pennsylvania State University, University Park.

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