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Probability expression for changeable and changeless uncertainties: an implicit test.

Wang Y, Du XL, Rao LL, Li S - Front Psychol (2014)

Bottom Line: We found that the "verbal-changeable" combination in implicit tasks was more compatible than the "numerical-changeable" combination.These results extend the domain of probability predictions and enrich our general understanding of communication with verbal and numerical probabilities.Given that the world around us is constantly changing, this "changeability" feature may play a major role in preparing for uncertainty.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences Beijing, China ; University of Chinese Academy of Sciences Beijing, China.

ABSTRACT
"Everything changes and nothing remains still."We designed three implicit studies to understand how people react or adapt to a rapidly changing world by testing whether verbal probability is better in expressing changeable uncertainty while numerical probability is better in expressing unchangeable uncertainty. We found that the "verbal-changeable" combination in implicit tasks was more compatible than the "numerical-changeable" combination. Furthermore, the "numerical-changeless" combination was more compatible than the "verbal-changeless" combination. Thus, a novel feature called "changeability" was proposed to describe the changeable nature of verbal probability. However, numerical probability is a better carrier of changeless uncertainty than verbal probability. These results extend the domain of probability predictions and enrich our general understanding of communication with verbal and numerical probabilities. Given that the world around us is constantly changing, this "changeability" feature may play a major role in preparing for uncertainty.

No MeSH data available.


Beauty score as a function of probability expression for person and computer. Error bars denote standard errors.
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Figure 2: Beauty score as a function of probability expression for person and computer. Error bars denote standard errors.

Mentions: As in Study 1, we summed the rating score corresponding to the four different font types for each animacy-probability pairing condition, which represented the overall beauty of the font types for each condition. An ANOVA was conducted with probability expression and animacy as the within-subjects factors. The analysis revealed that the main effects of probability expression and animacy were not significant. However, there was a significant interaction between probability expression and animacy [F(1, 102) = 61.533, p < 0.001, η2 = 0.376]. Simple effects analyses indicated that the beauty score in the PV (person–verbal) condition was significantly higher than the beauty score in the PN (person–numerical) condition (p < 0.001), whereas the beauty score in the CN (computer–numerical) condition was significantly higher than the beauty score in the CV (computer–verbal) condition (p < 0.001; Figure 2).


Probability expression for changeable and changeless uncertainties: an implicit test.

Wang Y, Du XL, Rao LL, Li S - Front Psychol (2014)

Beauty score as a function of probability expression for person and computer. Error bars denote standard errors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230050&req=5

Figure 2: Beauty score as a function of probability expression for person and computer. Error bars denote standard errors.
Mentions: As in Study 1, we summed the rating score corresponding to the four different font types for each animacy-probability pairing condition, which represented the overall beauty of the font types for each condition. An ANOVA was conducted with probability expression and animacy as the within-subjects factors. The analysis revealed that the main effects of probability expression and animacy were not significant. However, there was a significant interaction between probability expression and animacy [F(1, 102) = 61.533, p < 0.001, η2 = 0.376]. Simple effects analyses indicated that the beauty score in the PV (person–verbal) condition was significantly higher than the beauty score in the PN (person–numerical) condition (p < 0.001), whereas the beauty score in the CN (computer–numerical) condition was significantly higher than the beauty score in the CV (computer–verbal) condition (p < 0.001; Figure 2).

Bottom Line: We found that the "verbal-changeable" combination in implicit tasks was more compatible than the "numerical-changeable" combination.These results extend the domain of probability predictions and enrich our general understanding of communication with verbal and numerical probabilities.Given that the world around us is constantly changing, this "changeability" feature may play a major role in preparing for uncertainty.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences Beijing, China ; University of Chinese Academy of Sciences Beijing, China.

ABSTRACT
"Everything changes and nothing remains still."We designed three implicit studies to understand how people react or adapt to a rapidly changing world by testing whether verbal probability is better in expressing changeable uncertainty while numerical probability is better in expressing unchangeable uncertainty. We found that the "verbal-changeable" combination in implicit tasks was more compatible than the "numerical-changeable" combination. Furthermore, the "numerical-changeless" combination was more compatible than the "verbal-changeless" combination. Thus, a novel feature called "changeability" was proposed to describe the changeable nature of verbal probability. However, numerical probability is a better carrier of changeless uncertainty than verbal probability. These results extend the domain of probability predictions and enrich our general understanding of communication with verbal and numerical probabilities. Given that the world around us is constantly changing, this "changeability" feature may play a major role in preparing for uncertainty.

No MeSH data available.