What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low

Research on verbal probabilities and standard scales issued by national and international authorities suggest that only events with probabilities above 60% should be labelled “likely”. We find, however, that when people apply this term to continuous variables, like expected costs, it describes the most likely (modal) outcome or interval, regardless of actual probabilities, which may be quite small. This was demonstrated in six studies in which lay participants (N = 2,228) were shown probability distributions from various domains and asked to generate or to select “likely” outcome intervals. Despite having numeric and graphically displayed information available, participants judged central, low-probability segments as “likely” (as opposed to equal or larger segments in the tails) and subsequently overestimated the chances of these outcomes. We conclude that high-probability interpretations of “likely” are only valid for binary outcomes but not for distributions of graded variables or multiple outcomes

Top scores are possible, bottom scores are certain (and middle scores are not worth mentioning): A pragmatic view of verbal probabilities

In most previous studies of verbal probabilities, participants are asked to translate expressions such as possible and not certain into numeric probability values. This probabilistic translation approach can be contrasted with a novel which-outcome (WO) approach that focuses on the outcomes that people naturally associate with probability terms. The WO approach has revealed that, when given bell-shaped distributions of quantitative outcomes, people tend to associate certainty with minimum (unlikely) outcome magnitudes and possibility with (unlikely) maximal ones. The purpose of the present paper is to test the factors that foster these effects and the conditions in which they apply. Experiment 1 showed that the association of probability term and outcome was related to the association of scalar modifiers (i.e., it is certain that the battery will last at least…, it is possible that the battery will last up to…). Further, we tested whether this pattern was dependent on the frequency (e.g., increasing vs. decreasing distribution) or the nature of the outcomes presented (i.e., categorical vs. continuous). Results showed that despite being slightly affected by the shape of the distribution, participants continue to prefer to associate possible with maximum outcomes and certain with minimum outcomes. The final experiment provided a boundary condition to the effect, showing that it applies to verbal but not numerical probabilities

Responsibility judgments of wins and losses in the 2013 chess championship

We report two studies on the perceived responsibility of opponents competing for a goal that can be attained by only one of them. Responsibility judgments were collected in seven samples of lay people and experts before, during, and after the World Chess Championship in 2013. Participants assessed the responsibility of the two players, their supporting teams, local conditions, and chance factors for four hypothetical outcomes (large and small loss/win for each player), along with probabilities for these outcomes, demonstrating subadditivity (sums exceeding 100%) in all samples, even among chess experts. The winner was consistently perceived to be more responsible than the loser, and more for outcomes with large than small margins. There was also an effect of focal player, as Carlsen was given more responsibility both for losses and wins than Anand, by the present (Norwegian) pro-Carlsen samples. However, this effect could be modified by describing the outcomes as Anand’s (rather than Carlsen’s) wins and losses. Thus the study adds to the valence framing literature by showing how responsibility judgments are affected by the way outcomes are framed

Combining verbal forecasts: The role of directionality and the reinforcement effect

Recent research has shown that when people combine verbal probabilistic forecasts from two sources, they are not simply averaged but can reinforce each other; so when two advisors both said an event was “rather likely,” some listeners concluded that the event was “quite likely”. Conversely, when both said the event was “rather unlikely,” people concluded that it was “quite unlikely.” The present studies demonstrate that the direction of this effect is not evoked by high versus low probabilities, but by the directionality of verbal probability expressions. Some phrases are affirmative, directed towards occurrences (“there is a chance”), whereas others are negations, pointing to the possibility that the event might not occur (“it is not certain”). Two positive phrases are perceived to reinforce each other, even when they convey low probabilities, resulting in a higher combined probability estimate, whereas two negative phrases do the opposite, regardless of the probabilities they convey. We show that this effect occurs both for equal and unequal verbal phrases, regardless of the probability equivalents of the expressions. We also found a positive, but weaker, reinforcement effect of numerical probabilities

When do past events require explanation? Insights from social psychology

Some past events incite more wonder about their causes than do others. For example, negative events require explanation more than positive events. We review social psychologists’ theoretical and empirical insights on what kinds of past events “beg explanation.” We draw on attribution theory that became popular among psychologists from the 1960s onward, on research on counterfactual reasoning, and on conversational and discursive critiques of attribution theory. We argue that factors predicting what is or is not perceived as requiring explanation are culturally and historically grounded, and that accordingly, what begs explanation varies between contexts and can change over time. Yet, drawing on the distinction between content and process, we argue that there are recognizable patterns across time and space. Specifically, we propose the relationship between events and background expectations as a rather stable predictor of what begs explanation—and as a level of analysis that can unite seemingly disparate approaches

Top scores are possible, bottom scores are certain (and middle scores are not worth mentioning) : a pragmatic view of verbal probabilities

In most previous studies of verbal probabilities, participants are asked to translate expressions such as possible and not certain into numeric probability values. This probabilistic translation approach can be contrasted with a novel which-outcome (WO) approach that focuses on the outcomes that people naturally associate with probability terms. The WO approach has revealed that, when given bell-shaped distributions of quantitative outcomes, people tend to associate certainty with minimum (unlikely) outcome magnitudes and possibility with (unlikely) maximal ones. The purpose of the present paper is to test the factors that foster these effects and the conditions in which they apply. Experiment 1 showed that the association of probability term and outcome was related to the association of scalar modifiers (i.e., it is certain that the battery will last at least..., it is possible that the battery will last up to...). Further, we tested whether this pattern was dependent on the frequency (e.g., increasing vs. decreasing distribution) or the nature of the outcomes presented (i.e., categorical vs. continuous). Results showed that despite being slightly affected by the shape of the distribution, participants continue to prefer to associate possible with maximum outcomes and certain with minimum outcomes. The final experiment provided a boundary condition to the effect, showing that it applies to verbal but not numerical probabilities

Variants of verbal uncertainty

We suggest that speakers can communicate the source of their uncertainty by framing their prediction with either a personal mode �I am uncertain that the team will win� or with an impersonal mode �It is uncertain that the team will win�. We studied the effect of such mode on how recipients judge the prediction. We found that participants judged impersonal prediction more informative, and more based on statistical information than personal prediction. In addition participants were more willing to bet according to impersonal prediction. Findings support the existence of variants of uncertainty and that uncertain claims convey more than a probability

Forecasting forecasts: The trend effect

People often make predictions about the future based on trends they have observed in the past. Revised probabilistic forecasts can be perceived by the public as indicative of such a trend. In five studies, we describe experts who make probabilistic forecasts of various natural events (effects of climate changes, landslide and earthquake risks) at two points in time. Prognoses that have been upgraded or downgraded from T1 to T2 were in all studies expected to be updated further, in the same direction, later on (at T3). Thus, two prognoses were in these studies enough to define a trend, forming the basis for future projections. This “trend effect” implies that non-experts interpret recent forecast in light of what the expert said in the past, and think, for instance, that a “moderate” landslide risk will cause more worry if it has previously been low than if it has been high. By transcending the experts’ most recent forecasts the receivers are far from conservative, and appear to know more about the experts’ next prognoses than the experts themselves