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Uncategorized / 26.08.2020

Here, we're just setting a few options. Now, we're preparing our data for the codebook. Create codebook Metadata Description Dataset name: results The dataset has N=28 rows and 29 columns. 0 rows have no missing values on any column. Metadata for search engines Date published: 2020-08-26 x session created modified ended expired BFIK_open_2 BFIK_agree_4R BFIK_extra_2 BFIK_agree_1R BFIK_open_1 BFIK_neuro_2R BFIK_consc_3 BFIK_consc_4 BFIK_consc_2R BFIK_agree_3R BFIK_extra_3R BFIK_neuro_3 BFIK_neuro_4 BFIK_agree_2 BFIK_consc_1 BFIK_open_4 BFIK_extra_4 BFIK_extra_1R BFIK_open_3 BFIK_agree BFIK_open BFIK_consc BFIK_extra BFIK_neuro Codebook table { "name": "results", "datePublished": "2020-08-26", ...

Uncategorized / 26.08.2020

This document describes the labels and content of variables in the data. Codebook for Choice Data Metadata Description Dataset name: Human risky choices with goals Repeated binary choices by adult humans among a high- and a low-variance two-outcome lottery, who were given a point goal to reach after a certain...

Uncategorized / 23.06.2018

We do it every day: correctly classifying people, objects, words. What seems easy for humans is computationally very complex. Together with Jonathan D. Nelson and Björn Meder (both Center for Adaptive Behavior and Cognition, MPIB Berlin) I hypothesized and found that a relatively simple statistical...