# Partition-primed Probability Judgement Task for Car Dealership

### Description

In this study participants were asked to judge how likely it is that a customer trades in a coupe or that a customer buys a car form a specific salesperson out of four possible salespersons.

### Usage

1 |

### Format

A data frame with 155 observations on the following 3 variables.

`task`

a factor with levels

`Car`

and`Salesperson`

indicating the condition.`probability`

a numeric vector of the estimated probability.

`NFCCscale`

a numeric vector of the NFCC scale.

### Details

All participants in the study were undergraduate students at The Australian National University, some of whom obtained course credit in first-year Psychology for their participation in the study.

The NFCC scale is a combined scale of the Need for Closure and Need for Certainty scales which are strongly correlated.

For `task`

the questions were:

- Car
What is the probability that a customer trades in a coupe?

- Salesperson
What is the probability that a customer buys a car from Carlos?

### Source

Taken from http://dl.dropbox.com/u/1857674/betareg/betareg.html.

### References

Smithson, M., Merkle, E.C., and Verkuilen, J. (in press). Beta
Regression Finite Mixture Models of Polarization and
Priming. *Journal of Educational and Behavioral Statistics*.

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

### Examples

1 2 3 4 5 6 | ```
data("CarTask", package = "betareg")
library("flexmix")
car_betamix <- betamix(probability ~ 1, data = CarTask, k = 3,
extra_components = list(extraComponent(type = "uniform", coef = 1/2,
delta = 0.01), extraComponent(type = "uniform", coef = 1/4, delta = 0.01)),
FLXconcomitant = FLXPmultinom(~ task))
``` |

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