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id int64 1 200 | session int64 1 28 | loss_aversion_intensity float64 0.09 0.97 | recency_bias_strength float64 0.14 0.98 | overconfidence_score float64 0.1 1 | anchoring_sensitivity float64 0.08 1 | choice_complexity float64 0 1 | cognitive_load float64 0.15 1 | debiasing_support float64 0.08 0.85 | biastack_index float64 0.33 0.82 |
|---|---|---|---|---|---|---|---|---|---|
1 | 22 | 0.346382 | 0.464626 | 0.736186 | 0.294183 | 0.529202 | 0.526348 | 0.264399 | 0.51601 |
2 | 9 | 0.304109 | 0.313998 | 0.449577 | 0.386289 | 0.413782 | 0.369228 | 0.845904 | 0.334337 |
3 | 16 | 0.437788 | 0.506391 | 0.591858 | 0.392616 | 0.30897 | 0.511423 | 0.425471 | 0.477895 |
4 | 5 | 0.828178 | 0.467032 | 0.526308 | 0.600436 | 0.648422 | 0.31794 | 0.278083 | 0.603671 |
5 | 23 | 0.789999 | 0.91638 | 0.697329 | 0.707837 | 0.519545 | 0.603936 | 0.257528 | 0.72083 |
6 | 27 | 0.527043 | 0.76454 | 0.481124 | 0.791647 | 0.574653 | 0.684415 | 0.648724 | 0.587384 |
7 | 20 | 0.513134 | 0.161488 | 0.56723 | 0.429067 | 0.147933 | 0.475768 | 0.278208 | 0.444785 |
8 | 15 | 0.483733 | 0.516903 | 0.613958 | 0.431503 | 0.494952 | 0.373135 | 0.275086 | 0.52596 |
9 | 18 | 0.311176 | 0.817235 | 0.984282 | 0.611711 | 1 | 0.752156 | 0.545255 | 0.676882 |
10 | 13 | 0.809591 | 0.847396 | 0.693466 | 0.71502 | 0.800215 | 0.728025 | 0.218965 | 0.769904 |
11 | 2 | 0.476903 | 0.387917 | 0.415199 | 0.623382 | 0.796405 | 1 | 0.519745 | 0.577962 |
12 | 4 | 0.752121 | 0.873558 | 0.568441 | 0.815781 | 0.682334 | 0.72117 | 0.497835 | 0.700238 |
13 | 21 | 0.410376 | 0.270387 | 0.437798 | 0.527726 | 0.944493 | 0.741023 | 0.27601 | 0.564995 |
14 | 16 | 0.422878 | 0.517867 | 0.644703 | 0.691175 | 0.014203 | 0.50212 | 0.311882 | 0.5077 |
15 | 25 | 0.599128 | 0.31512 | 0.569966 | 0.629075 | 0.547331 | 0.69329 | 0.166911 | 0.601995 |
16 | 9 | 0.683901 | 0.455678 | 0.441832 | 0.675528 | 0.682245 | 0.783277 | 0.283893 | 0.633767 |
17 | 2 | 0.804642 | 0.674394 | 0.676384 | 0.728835 | 0.20998 | 0.569321 | 0.503814 | 0.608887 |
18 | 7 | 0.832488 | 0.923806 | 0.322563 | 0.586196 | 0.518798 | 0.517609 | 0.444576 | 0.619644 |
19 | 10 | 0.444436 | 0.260819 | 0.489419 | 0.278325 | 0.568543 | 0.777727 | 0.366996 | 0.48683 |
20 | 13 | 0.75264 | 0.547809 | 0.710787 | 0.081389 | 0.525279 | 0.491353 | 0.272285 | 0.561503 |
21 | 8 | 0.916525 | 0.702513 | 0.806558 | 0.838657 | 0.648398 | 0.50703 | 0.502908 | 0.711842 |
22 | 17 | 0.896001 | 0.411009 | 0.588234 | 0.547525 | 0.380083 | 0.488492 | 0.383255 | 0.580736 |
23 | 22 | 0.805719 | 0.400752 | 0.822378 | 0.647667 | 0.680131 | 0.631191 | 0.544718 | 0.637145 |
24 | 1 | 0.877992 | 0.174945 | 0.284905 | 0.585932 | 0.316296 | 0.600657 | 0.177627 | 0.546062 |
25 | 12 | 0.46504 | 0.617251 | 0.439254 | 0.484543 | 0.687437 | 0.859789 | 0.49458 | 0.565988 |
26 | 11 | 0.950186 | 0.357258 | 0.664177 | 0.841598 | 0.456841 | 0.595771 | 0.627543 | 0.617765 |
27 | 21 | 0.930704 | 0.665234 | 0.711231 | 0.844694 | 0.44682 | 0.590044 | 0.311848 | 0.713017 |
28 | 25 | 0.707037 | 0.942594 | 0.483549 | 0.728469 | 0.639041 | 0.725411 | 0.32701 | 0.700325 |
29 | 22 | 0.783437 | 0.384968 | 0.615351 | 0.761251 | 0.485081 | 0.663104 | 0.303007 | 0.636939 |
30 | 15 | 0.673293 | 0.268004 | 0.33792 | 0.573557 | 0.467851 | 0.543888 | 0.663825 | 0.461517 |
31 | 7 | 0.685925 | 0.463859 | 0.668963 | 0.534563 | 0.446977 | 0.862134 | 0.282873 | 0.628734 |
32 | 20 | 0.486267 | 0.4777 | 0.791109 | 0.363165 | 0.617341 | 0.685712 | 0.510008 | 0.550769 |
33 | 20 | 0.656266 | 0.593848 | 0.875761 | 0.844488 | 0.341755 | 0.503759 | 0.250863 | 0.663425 |
34 | 10 | 0.516946 | 0.536629 | 0.464254 | 0.647972 | 0.700359 | 0.745329 | 0.393745 | 0.594373 |
35 | 1 | 0.418748 | 0.52538 | 0.536993 | 0.484963 | 0.592009 | 0.493196 | 0.571258 | 0.490825 |
36 | 17 | 0.369511 | 0.787449 | 0.506766 | 0.561533 | 0.119184 | 0.421946 | 0.179459 | 0.522539 |
37 | 25 | 0.610768 | 0.6981 | 0.682101 | 0.67606 | 0.335135 | 0.260147 | 0.213675 | 0.595061 |
38 | 7 | 0.676918 | 0.212582 | 0.562425 | 0.55441 | 0.925048 | 0.727129 | 0.286174 | 0.620437 |
39 | 14 | 0.686707 | 0.844527 | 0.856615 | 0.605912 | 0.857888 | 0.763749 | 0.624306 | 0.701302 |
40 | 8 | 0.846811 | 0.504056 | 0.383321 | 0.503648 | 0.757199 | 0.820502 | 0.324905 | 0.644509 |
41 | 20 | 0.802113 | 0.709883 | 0.62926 | 0.726414 | 0.938514 | 0.663242 | 0.329312 | 0.733079 |
42 | 20 | 0.626101 | 0.363142 | 0.537427 | 0.824445 | 0.608154 | 0.599362 | 0.613149 | 0.560998 |
43 | 9 | 0.642442 | 0.706239 | 0.558884 | 0.783413 | 0.44008 | 0.556127 | 0.390153 | 0.619555 |
44 | 26 | 0.40734 | 0.529515 | 0.478696 | 0.746926 | 0.653776 | 0.681397 | 0.551 | 0.551101 |
45 | 19 | 0.535939 | 0.373008 | 0.380659 | 0.683926 | 0.376655 | 0.729667 | 0.442455 | 0.519698 |
46 | 14 | 0.700909 | 0.452847 | 0.391766 | 0.737307 | 0.554619 | 0.562199 | 0.295588 | 0.594356 |
47 | 2 | 0.403863 | 0.817188 | 0.59199 | 0.497689 | 0.497853 | 0.51192 | 0.203057 | 0.58834 |
48 | 20 | 0.726932 | 0.873204 | 0.60716 | 0.566827 | 0 | 0.410674 | 0.658219 | 0.52142 |
49 | 20 | 0.911419 | 0.863218 | 0.550469 | 0.733679 | 0.367526 | 0.599202 | 0.619018 | 0.641651 |
50 | 25 | 0.915263 | 0.574644 | 0.479536 | 0.634601 | 0.384168 | 0.68026 | 0.358488 | 0.63155 |
51 | 12 | 0.428261 | 0.22523 | 0.622803 | 0.21273 | 0.237089 | 0.38089 | 0.583004 | 0.366471 |
52 | 13 | 0.089584 | 0.565695 | 0.475842 | 0.441531 | 0.546224 | 0.531099 | 0.275663 | 0.468927 |
53 | 22 | 0.631869 | 0.519277 | 0.349665 | 0.681293 | 0.57928 | 0.791513 | 0.246328 | 0.615852 |
54 | 21 | 0.679131 | 0.800018 | 0.349195 | 0.580816 | 0.52979 | 0.744824 | 0.341596 | 0.622746 |
55 | 27 | 0.475773 | 0.557399 | 0.901943 | 0.456317 | 0.580238 | 0.565113 | 0.558433 | 0.561924 |
56 | 13 | 0.62754 | 0.91413 | 0.744084 | 0.467273 | 0.545425 | 0.584507 | 0.356103 | 0.649141 |
57 | 21 | 0.4565 | 0.500451 | 0.718875 | 0.653333 | 0.506971 | 0.557055 | 0.250408 | 0.59196 |
58 | 9 | 0.745603 | 0.547016 | 0.331444 | 0.548414 | 0.497345 | 0.674299 | 0.370376 | 0.575308 |
59 | 20 | 0.664414 | 0.509278 | 0.68775 | 0.874972 | 0.224217 | 0.512666 | 0.475282 | 0.582055 |
60 | 17 | 0.649192 | 0.380495 | 0.903115 | 0.485785 | 1 | 0.608232 | 0.242859 | 0.6787 |
61 | 25 | 0.40443 | 0.561909 | 0.728658 | 0.574463 | 0.914313 | 0.737052 | 0.513494 | 0.609907 |
62 | 22 | 0.556898 | 0.563986 | 0.102628 | 0.447909 | 0.546575 | 0.544936 | 0.54127 | 0.460653 |
63 | 21 | 0.529639 | 0.36145 | 0.393017 | 0.507162 | 0.323594 | 0.559729 | 0.323216 | 0.486247 |
64 | 4 | 0.722057 | 0.711541 | 0.527373 | 0.730749 | 0.568597 | 0.702552 | 0.586313 | 0.624451 |
65 | 25 | 0.685463 | 0.762995 | 0.850258 | 0.511986 | 0.696312 | 0.414455 | 0.634509 | 0.612687 |
66 | 17 | 0.503757 | 0.536648 | 0.534805 | 0.88638 | 0.68354 | 0.754568 | 0.156409 | 0.672321 |
67 | 20 | 0.842971 | 0.313196 | 0.40752 | 0.624614 | 0.24732 | 0.408531 | 0.124502 | 0.558863 |
68 | 4 | 0.75753 | 0.981826 | 0.765301 | 0.945328 | 0.682715 | 0.77545 | 0.171101 | 0.820903 |
69 | 12 | 0.519086 | 0.598775 | 0.612127 | 0.536863 | 0.501867 | 0.373164 | 0.400845 | 0.538991 |
70 | 10 | 0.536996 | 0.409523 | 0.586091 | 0.468637 | 0.417326 | 0.540894 | 0.774728 | 0.452684 |
71 | 19 | 0.265292 | 0.463885 | 0.475337 | 0.247766 | 0.580829 | 0.792963 | 0.410391 | 0.473123 |
72 | 11 | 0.400082 | 0.431129 | 0.364975 | 0.303638 | 0.757185 | 0.880822 | 0.273736 | 0.538742 |
73 | 15 | 0.507973 | 0.29722 | 0.470186 | 0.333363 | 0.433067 | 0.379105 | 0.220776 | 0.467679 |
74 | 12 | 0.31459 | 0.545627 | 0.429725 | 0.673153 | 0.461808 | 0.699882 | 0.600681 | 0.490711 |
75 | 11 | 0.901877 | 0.375023 | 0.420251 | 0.57376 | 0.483586 | 0.500827 | 0.404287 | 0.567446 |
76 | 3 | 0.750056 | 0.813534 | 0.530159 | 0.538613 | 0.847117 | 0.859858 | 0.087655 | 0.749345 |
77 | 3 | 0.323732 | 0.286682 | 0.479302 | 0.627069 | 0.221317 | 0.43652 | 0.330845 | 0.439304 |
78 | 17 | 0.75547 | 0.519291 | 0.718489 | 0.399273 | 0.356439 | 0.370622 | 0.593765 | 0.517417 |
79 | 26 | 0.332033 | 0.571466 | 0.498152 | 0.472861 | 0.545882 | 0.706513 | 0.415886 | 0.519459 |
80 | 21 | 0.811675 | 0.36481 | 0.708757 | 0.783062 | 0.470902 | 0.473474 | 0.652957 | 0.574882 |
81 | 15 | 0.775043 | 0.436291 | 0.424334 | 0.361421 | 0.458276 | 0.667775 | 0.350285 | 0.549675 |
82 | 3 | 0.680062 | 0.223583 | 0.31412 | 0.389823 | 0.27623 | 0.436052 | 0.433078 | 0.428446 |
83 | 5 | 0.472717 | 0.597038 | 0.530242 | 0.678653 | 0.647134 | 0.746403 | 0.234837 | 0.62757 |
84 | 3 | 0.473254 | 0.193807 | 0.287473 | 0.598882 | 0.644193 | 0.61518 | 0.459534 | 0.474008 |
85 | 10 | 0.874596 | 0.85278 | 0.856701 | 0.71914 | 0.285958 | 0.546024 | 0.504164 | 0.676606 |
86 | 25 | 0.38124 | 0.798472 | 0.961866 | 0.395442 | 0.725098 | 0.632996 | 0.657444 | 0.588213 |
87 | 21 | 0.82138 | 0.653978 | 0.609587 | 0.422354 | 0.536986 | 0.464266 | 0.256017 | 0.623064 |
88 | 24 | 0.844137 | 0.652537 | 0.627386 | 0.721232 | 0.426496 | 0.352102 | 0.653157 | 0.581033 |
89 | 21 | 0.651856 | 0.374145 | 0.429576 | 0.447185 | 0.267701 | 0.557429 | 0.684476 | 0.44196 |
90 | 26 | 0.383734 | 0.427032 | 0.666851 | 0.453787 | 0.735785 | 0.396056 | 0.503601 | 0.500991 |
91 | 14 | 0.728247 | 0.322291 | 0.336194 | 0.562861 | 0.338923 | 0.583322 | 0.280853 | 0.527806 |
92 | 16 | 0.463882 | 0.829569 | 0.397493 | 0.556031 | 0.689636 | 0.594465 | 0.665474 | 0.540748 |
93 | 23 | 0.235363 | 0.516189 | 0.545788 | 0.329395 | 0.837808 | 0.489149 | 0.128317 | 0.535862 |
94 | 24 | 0.679577 | 0.700806 | 0.566233 | 0.819401 | 1 | 0.801357 | 0.522842 | 0.706934 |
95 | 4 | 0.721768 | 0.6631 | 0.989365 | 0.314299 | 0.89843 | 0.762285 | 0.258514 | 0.723189 |
96 | 24 | 0.464984 | 0.867905 | 0.983469 | 0.617917 | 0.688943 | 0.628341 | 0.752909 | 0.627006 |
97 | 22 | 0.22518 | 0.679285 | 0.546305 | 0.581671 | 0.472559 | 0.728873 | 0.196109 | 0.566343 |
98 | 23 | 0.376172 | 0.402231 | 0.444012 | 0.255657 | 0.506183 | 0.596235 | 0.131719 | 0.493192 |
99 | 27 | 0.755041 | 0.485106 | 0.424248 | 0.362617 | 0.583178 | 0.55766 | 0.37788 | 0.550423 |
100 | 12 | 0.83062 | 0.552728 | 0.666398 | 0.637078 | 0.446503 | 0.346523 | 0.208489 | 0.631185 |
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Biastack Economics Dataset
Dataset Description
Summary
Synthetic 200-row dataset for Biastack measurement and computational experiments.
Supported Tasks
- Economic analysis
- Behavioral Economics research
- Computational economics
Languages
- English (metadata and documentation)
- Python (code examples)
Dataset Structure
Data Fields
id: Unique observation idsession: Synthetic decision sessionloss_aversion_intensity: Estimated loss aversion strengthrecency_bias_strength: Weight on recent outcomesoverconfidence_score: Forecast overprecision proxyanchoring_sensitivity: Sensitivity to initial reference valueschoice_complexity: Decision menu complexitycognitive_load: Contextual cognitive burdendebiasing_support: Strength of debiasing interventionbiastack_index: Composite term index
Data Splits
- Full dataset: 200 examples
Dataset Creation
Source Data
Synthetic data generated for demonstrating Biastack applications.
Data Generation
Channels are sampled from controlled distributions with correlated structure. The term index is computed from normalized channels and directional weights.
Considerations
Social Impact
Research-only synthetic data for method development and reproducibility testing.
Additional Information
Licensing
MIT License - free for academic and commercial use.
Citation
@dataset{biastack2026, title={{Biastack Economics Dataset}}, author={{Economic Research Collective}}, year={{2026}} }
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