# ImpreciseTask

##### Imprecise Probabilities for Sunday Weather and Boeing Stock Task

In this study participants were asked to estimate upper and lower probabilities for event to occur and not to occur.

- Keywords
- datasets

##### Usage

`data(ImpreciseTask)`

##### Details

All participants in the study were either first- or second-year undergraduate students in psychology, none of whom had a strong background in probability or were familiar with imprecise probability theories.

For the sunday weather task see `WeatherTask`

. For the Boeing
stock task participants were asked to estimate the probability that
Boeing's stock would rise more than those in a list of 30 companies.

For each task participants were asked to provide lower and upper estimates for the event to occur and not to occur.

##### Format

A data frame with 242 observations on the following 3 variables.

`task`

a factor with levels

`Boeing stock`

and`Sunday weather`

.`location`

a numeric vector of the average of the lower estimate for the event not to occur and the upper estimate for the event to occur.

`difference`

a numeric vector of the differences of the lower and upper estimate for the event to occur.

##### References

Smithson, M., Merkle, E.C., and Verkuilen, J. (2011). Beta
Regression Finite Mixture Models of Polarization and Priming.
*Journal of Educational and Behavioral Statistics*, **36**(6), 804--831.
10.3102/1076998610396893

Smithson, M., and Segale, C. (2009). Partition Priming in Judgments of
Imprecise Probabilities. *Journal of Statistical Theory and
Practice*, **3**(1), 169--181.

##### Examples

```
# NOT RUN {
data("ImpreciseTask", package = "betareg")
library("flexmix")
wt_betamix <- betamix(location ~ difference * task, data = ImpreciseTask, k = 2,
extra_components = extraComponent(type = "betareg", coef =
list(mean = 0, precision = 8)),
FLXconcomitant = FLXPmultinom(~ task))
# }
```

*Documentation reproduced from package betareg, version 3.1-3, License: GPL-2 | GPL-3*