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How important is it to ask pointed questions?

Source: R/data-ask.R
ask.Rd

In this experiment, each individual was asked to be a seller of an iPod (a product commonly used to store music on before smart phones...). They participant received $10 + 5% of the sale price for participating. The iPod they were selling had frozen twice in the past inexplicably but otherwise worked fine. The prospective buyer starts off and then asks one of three final questions, depending on the seller's treatment group.

Usage

ask

Format

A data frame with 219 observations on the following 3 variables.

question_class

The type of question: general, pos_assumption, and neg_assumption.

question

The question corresponding to the question.class

response

The classified response from the seller, either disclose or hide.

Source

Minson JA, Ruedy NE, Schweitzer ME. There is such a thing as a stupid question: Question disclosure in strategic communication.

Details

The three possible questions:

  • General: What can you tell me about it?

  • Positive Assumption: It doesn't have any problems, does it?

  • Negative Assumption: What problems does it have?

The outcome variable is whether or not the participant discloses or hides the problem with the iPod.

Examples


library(dplyr)
library(ggplot2)

# Distribution of responses based on question type
ask |>
  count(question_class, response)
#> # A tibble: 6 × 3
#>   question_class response     n
#>   <chr>          <chr>    <int>
#> 1 general        disclose     2
#> 2 general        hide        71
#> 3 neg_assumption disclose    36
#> 4 neg_assumption hide        37
#> 5 pos_assumption disclose    23
#> 6 pos_assumption hide        50

# Visualize relative frequencies of responses based on question type
ggplot(ask, aes(x = question_class, fill = response)) +
  geom_bar(position = "fill")


# Perform chi-square test
(test <- chisq.test(table(ask$question_class, ask$response)))
#> 
#> 	Pearson's Chi-squared test
#> 
#> data:  table(ask$question_class, ask$response)
#> X-squared = 40.128, df = 2, p-value = 1.933e-09
#> 

# Check the test's assumption around sufficient expected observations
# per table cell.
test$expected
#>                 
#>                  disclose     hide
#>   general        20.33333 52.66667
#>   neg_assumption 20.33333 52.66667
#>   pos_assumption 20.33333 52.66667