Assumption Measurement Applications for the Individual Decision Maker

Cover Assumption Measurement Applications for the Individual Decision Maker
Assumption Measurement Applications for the Individual Decision Maker
Jarrod W Jarrod Whitfield Wilcox
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Putting aside this interesting detour, let us return to the general application. In our illustration, the next question is whether the decision- makers actually use this information in making their ratings. If we look at the suitability ratings, Y, we find corr. (Yp^, Y^^) = 0. 408, R^ = 0. 1665 corr. (Y22. Y22) = 0. 040, R^ = . 0016 corr. (Y^g, Y^g) =0. 441 R^ = . 1945 Table 5 Significant at 0. 10 level R^ = . 0016 Not significant R^ = . 1945 Significant at 0. 10 level.
Thus, it appears possib
...le that Decision-makers 07 and 38 are using a greater degree of valid information than that measured through the factor attributes F, obtained in the larger study. It is, however, quite likely that Decision- maker 22 is mis-using (using a lesser degree of) this information potentially available to him. In the larger study, the following was obtained as a measure of his assumptions: ^22 = 2873 + (-1. 94)F22_i + (-2. 93)F22_3 + (-1. 54)F22_6 In fact, he placed reliance not only on F„„ _, which our evidence indicates was helpful, but also on F„„ .

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