4,588 responses from 1,147 respondents to 4 items.
The scored version of this table is himmelstein-berlin_numeracy-2025.
One of 8 tables from the same source. The others are listed under Related tables.
| Description | This dataset measures numeracy with the Berlin Numeracy Test. |
|---|---|
| Reference | Himmelstein, Mark, Sophie Ma Zhu, Nikolay Petrov, Ezra Karger, Jessica Helmer, Sivan Livnat, Amory Bennett, Page Hedley, and Phil Tetlock. “The Forecasting Proficiency Test: A General Use Assessment of Forecasting Ability”. PsyArXiv, November 23, 2025. doi:10.31234/osf.io/a7kdx_v8. |
| DOI | 10.31234/osf.io/a7kdx_v8 |
| Licence | CC BY 4.0 |
| Source data | https://github.com/forecastingresearch/fpt/tree/main/data_cognitive_tasks |
| Responses | 4,588 |
|---|---|
| Respondents | 1,147 |
| Items | 4 |
| Response categories | 4 |
| Responses per respondent | 4 |
iditemresptext
id, item, resp are defined in the IRW data standard and mean the same in every table. For the other columns, including what item codes and covariate values stand for, any codebook is the one released with the source data.
Or load it directly in R or Python:
# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("himmelstein-berlin_numeracy-2025_nom", source = "nom")
# Python (needs a free Redivis account)
pip install irw
import irw
df = irw.fetch("himmelstein-berlin_numeracy-2025_nom", source="nom")
@article{Himmelstein_2025, title={The Forecasting Proficiency Test: A General Use Assessment of Forecasting Ability}, url={http://dx.doi.org/10.31234/osf.io/a7kdx_v8}, DOI={10.31234/osf.io/a7kdx_v8}, publisher={Center for Open Science}, author={Himmelstein, Mark and Zhu, Sophie Ma and Petrov, Nikolay and Karger, Ezra and Helmer, Jessica and Livnat, Sivan and Bennett, Amory and Hedley, Page and Tetlock, Phil}, year={2025}, month=Nov }
| IRW version | v540 |
|---|---|
| Redivis dataset | irw_nominal v4.1 |
| Redivis dataset DOI | 10.57761/9hzd-dc70 |
| Manifest pin for this IRW version | v4.0 |
| Metadata source | irw_meta v37.0 |