Exact(47)
For example, assume A is a frequent itemset which contains items ((P'_3D, P'_1Y, P'_4S, P_1Y, P_4S)).
The similarity between A and B is 2 because only items (P'_3D) and (P'_1Y) are present in both.
Likewise, naïve ideas differed significantly between experts and novices for each of the individual items (P < 0.01 for all items except for the salamander item, in which P > 0.05).
The image quality of the 3DX was better than the multidetector CT for all items (P <.01).
In contrary, students from schools A and B performed significantly better on these items (p < .05).05
The "outer fringe" of some knowledge state K is the set of all problems (or items) p such that adding p to K forms another knowledge state.
Similar(13)
(3) Analysis of the test items: p-value < 0.0001.
For items in class B (similar items) p-value represents comparison of students and facilitators with Mann-Whitney's test.
Further, we observed a significant main effect of item type [F 2,142) = 27.20 and p <.001], indicating that confidence was higher for the no-filler items compared to the contact items and the yes-filler items,p<.003.003
Perceived needs for these items were seen as much greater among Palestinian refugees from Syria, as measured by the number of needed items [ p <0.001].> -wrap-foot> *Chi-squared testatisticalical significance if p-value of <0.05.
The probability of finding both items can be predicted from the probabilities of finding the single items: P find 1 specific target) = 96.4%, P categorical) = 63.4%; 96.4%*63.4% = 61.4%, actual P find both) = 61.6%; t(11) = 0.8, p = 0.47).
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