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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 objects with different changeability in the water scenario (A) and the die scenario (B). Error bars denote standard errors.
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Figure 3: Beauty score as a function of probability expression for objects with different changeability in the water scenario (A) and the die scenario (B). Error bars denote standard errors.

Mentions: For the font-type rating task, we summed the rating score that corresponded to the four different font types for each changeability-probability pairing condition, which represented the overall beauty of the font type for each condition. Thereafter, an ANOVA was conducted for each scenario with probability expression and changeability as within-subjects factors. The analysis revealed that the probability expression and changeability in both scenarios had no main effects. There were significant interactions between probability expression and changeability for the water scenario [F(1, 96) = 11.264, p = 0.001, η2 = 0.105] and the die scenario [F(1, 96) = 7.681, p = 0.007, η2 = 0.074] (Figure 3). In the water scenario, a simple effects analysis indicated that the beauty score in the RV (river–verbal) condition was significantly higher than the beauty score in the RN (river–numerical) condition (p = 0.002), while the beauty score in the PN (pool–numerical) condition was significantly higher than the beauty score in the PV (pool–verbal) condition (p = 0.046; Figure 3A). Similar results were found for the die scenario, i.e., the beauty score in the RV (rolling die–verbal) condition was significantly higher than the beauty score in the RN (rolling die–numerical) condition (p = 0.038), while the beauty score in the SN (settled die–numerical) condition was significantly higher than the beauty score in the SV (settled die–verbal) condition (p = 0.017; Figure 3B). The sentences in the die scenario received higher beauty scores than those in the water scenario. This may be because different font types were used in the two scenarios, as shown in Tables 3, 4.


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 objects with different changeability in the water scenario (A) and the die scenario (B). Error bars denote standard errors.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: Beauty score as a function of probability expression for objects with different changeability in the water scenario (A) and the die scenario (B). Error bars denote standard errors.
Mentions: For the font-type rating task, we summed the rating score that corresponded to the four different font types for each changeability-probability pairing condition, which represented the overall beauty of the font type for each condition. Thereafter, an ANOVA was conducted for each scenario with probability expression and changeability as within-subjects factors. The analysis revealed that the probability expression and changeability in both scenarios had no main effects. There were significant interactions between probability expression and changeability for the water scenario [F(1, 96) = 11.264, p = 0.001, η2 = 0.105] and the die scenario [F(1, 96) = 7.681, p = 0.007, η2 = 0.074] (Figure 3). In the water scenario, a simple effects analysis indicated that the beauty score in the RV (river–verbal) condition was significantly higher than the beauty score in the RN (river–numerical) condition (p = 0.002), while the beauty score in the PN (pool–numerical) condition was significantly higher than the beauty score in the PV (pool–verbal) condition (p = 0.046; Figure 3A). Similar results were found for the die scenario, i.e., the beauty score in the RV (rolling die–verbal) condition was significantly higher than the beauty score in the RN (rolling die–numerical) condition (p = 0.038), while the beauty score in the SN (settled die–numerical) condition was significantly higher than the beauty score in the SV (settled die–verbal) condition (p = 0.017; Figure 3B). The sentences in the die scenario received higher beauty scores than those in the water scenario. This may be because different font types were used in the two scenarios, as shown in Tables 3, 4.

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.