In an experiment, sixty participants were assigned to three groups namely, A, B and C. None from the group C turned up for the experiment. The resulting data can be analyzed by :
Wilcoxon rank sum test
Sixty participants were split among three groups, so each person belonged to only one group: this is an independent-groups (between-subjects) design. When nobody from group C turned up, only two independent groups, A and B, remain with data.
Two independent samples can be compared with the Wilcoxon rank sum test (equivalent to the Mann–Whitney U test), the non-parametric counterpart of the independent-samples t test. It ranks all scores together and compares the rank sums of the two groups, and it needs no assumption of normality, which suits small and uneven groups.
A dependent (repeated-measures) one-way ANOVA requires the same participants to be measured under every condition, and with only two groups an ANOVA is unnecessary anyway. A dependent t test needs paired or matched scores, which independent groups do not provide. A mixed-group ANOVA needs both a between-subjects and a within-subjects factor, which this design does not have.
Wilcoxon rank sum test option is correct.
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