9,099 responses from 1,189 respondents to 9 items.
| Description | This dataset measures accuracy on a number-series task where participants identify the next number in the sequence. |
|---|---|
| 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 | 9,099 |
|---|---|
| Respondents | 1,189 |
| Items | 9 |
| Response categories | 2 |
| Responses per respondent | 7.653 |
| Responses per item | 1,011 |
| Density | 0.850 |
| Longitudinal | TRUE |
| age range | Adult (18+) |
|---|---|
| construct type | Cognitive/educational |
| measurement tool | Survey/questionnaire |
| item format | Slider/continuous |
| primary language(s) | eng |
| construct name | Accuracy on a number-series task where participants identify the next number in the sequence |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | This dataset measures accuracy on a number-series task where participants identify the next number in the sequence. |
|---|---|
| Mean words per item | 5.889 |
| Mean characters per item | 25.333 |
| Mean characters per response | NaN |
| Flesch-Kincaid grade level | -1.103 |
cov_session_ididitemresprtwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("himmelstein-number_series-2025")
# Python
pip install irw
import irw
df = irw.fetch("himmelstein-number_series-2025")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |