Attraction Effect: Bets Experiment

• All Participants
• Statistics

Participant Statistics

No of Participants	73
Pairs /participant	10
No of Pairs	730

Analysis 1: contingency tables (descriptive statistics)

	Attraction Effect
	Repulsion Effect

	A	B	D
A	TARGET COMPETITOR 417 (57.123287671233 %)	COMPETITOR COMPETITOR 53 (7.2602739726027 %)	COMPETITOR DECOY 12 (1.6438356164384 %)
B	TARGET TARGET 165 (22.602739726027 %)	COMPETITOR TARGET 71 (9.7260273972603 %)	TARGET DECOY 5 (0.68493150684932 %)
D	DECOY TARGET 7 (0.95890410958904 %)	DECOY COMPETITOR 0 (0 %)	DECOY DECOY 0 (0 %)

Analysis 2: inferential statistics (for R code)

ScoresA (10):

+1	chose Target
+0	chose Competitor
+0.5	chose Decoy

ScoresB (10):

+1	chose Competitor
+0	chose Target
+0.5	chose Decoy

Observation = ScoreA/10 - ScoreB/10

observation = 0	no bias (no attraction or repulsion effect)
observation > 0	attraction effect
observation < 0	repulsion Effect

observations <- c(0.1, 0, -0.1, -0.2, -0.2, -0.25, 0.7, 0.2, 0.1, 0.1, 0.2, -0.2, 0.4, 0.2, 0.25, -0.1, -0.2, -0.2, 0, 1, 0.1, 0.1, 0.1, 0.1, 0.3, 0.4, 0, 0, 0, -0.1, 0, -0.1, 0.4, 0.2, 0.1, 0.1, 0.1, 0.2, -0.1, 0, 0.4, 0.05, 0.3, 0.35, 0.1, 0.35, 0.6, 0.1, -0.1, 0.1, 0, -0.2, 0.3, 0.25, 0.2, 0.1, 0.4, 0.1, 0.8, 0.4, -0.1, 0.2, 0.2, -0.1, 0.25, 0.6, 0.5, -0.1, 0.15, -0.1, 0.9, 0.4, 0.1)

Analysis 3: analyze strategies (for R code)

StrategyScore (10):

+1	AA and BB
+0	AB and BA
+0.5	D anywhere

Observation = StrategyScore/10

observation > 0.5	the participant is "consistent" within pairs -> they most likely use the attributes in their choice
observation < 0.5	the participant is inconsistent within pairs -> they most likely use a strategy that takes into account the position of the decoy.

observations <- c(0.9, 0.8, 0.9, 0.8, 0.6, 0.65, 0.3, 0.8, 0.9, 0.9, 0.4, 0.8, 0.6, 0.8, 0.65, 0.9, 0.8, 0.6, 0.8, 0, 0.5, 0.9, 0.5, 0.9, 0.7, 0.6, 0.8, 0.6, 0.8, 0.5, 0.8, 0.7, 0.6, 0.8, 0.9, 0.9, 0.9, 0.8, 0.7, 1, 0.6, 0.95, 0.5, 0.65, 0.9, 0.45, 0.4, 0.7, 0.9, 0.7, 0.8, 0.6, 0.5, 0.25, 0.8, 0.9, 0.6, 0.9, 0.2, 0.6, 0.9, 0.6, 0.8, 0.9, 0.75, 0.2, 0.5, 0.7, 0.85, 0.7, 0.1, 0.4, 0.9)