heiDATA

Share Dataverse

Share this dataverse on your favorite social media networks.

Metrics

8,942 Downloads

heiDATA is an institutional repository for research data of Heidelberg University. It is managed by the Competence Centre for Research Data, a joint institution of the University Library and the Computing Centre. If you are interested in publishing your data here, please see our author instructions and get in touch with us.

Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

1 to 10 of 849 Results

Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] Apr 18, 2018 - AWI Experimental Economics Trautmann, Stefan T.; Wakker, Peter P., 2018, "Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]", doi:10.11588/data/HNN1FW, heiDATA, V1 The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions tha...
graphs_for_experiment.zip Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] ZIP Archive - 71.1 KB - MD5: ce4693156e2003f4803565050f338c00 bmp-Files
TrautmannWakker_Experiment_data.xlsx Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] MS Excel (XLSX) - 19.8 KB - MD5: 726c22409146d097002a124f6c4fc991 Data
TrautmannWakker_Experiment_Instructions.pdf Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] Adobe PDF - 105.5 KB - MD5: d5848f1f6416e7bdd398762644d454d1 Documentation Experiment Instructions
TrautmannWakker_onlineappendix.pdf Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] Adobe PDF - 331.7 KB - MD5: 2b6021a539615f6772b733206204e5ce Documentation
zTree_export.zip Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] ZIP Archive - 21.4 KB - MD5: df6a0e82e87934c193f2c581fefc5463 Code zTree files (exported for long term preservation)
zTree.zip Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset] ZIP Archive - 19.4 KB - MD5: 5e4dea577d2674cd3a6b0af40c1f1860 Code zTree files (original)
MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets Apr 16, 2018 - GIScience and 3D Spatial Data Processing Herfort, Benjamin, 2018, "MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets", doi:10.11588/data/3GYJUG, heiDATA, V1 MapSwipe is a mobile crowdsourcing application designed for smartphones and tablets to generate geographic information from satellite imagery. Data from 55 projects containing more than nine million tasks and more than 30 million individual classification results contributed by a...
global_datasets.zip Apr 16, 2018 - MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets ZIP Archive - 297.4 MB - MD5: 605e8b210f7a7e0dd8858f21bdb7d0de Data
laos_datasets.zip Apr 16, 2018 - MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets ZIP Archive - 138.8 MB - MD5: 54433b68ddd165b749baa3843a8ab58e Data

Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

Apr 18, 2018 - AWI Experimental Economics

Trautmann, Stefan T.; Wakker, Peter P., 2018, "Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]", doi:10.11588/data/HNN1FW, heiDATA, V1

The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions tha...

graphs_for_experiment.zip

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

ZIP Archive - 71.1 KB - MD5: ce4693156e2003f4803565050f338c00

bmp-Files

TrautmannWakker_Experiment_data.xlsx

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

MS Excel (XLSX) - 19.8 KB - MD5: 726c22409146d097002a124f6c4fc991

Data

TrautmannWakker_Experiment_Instructions.pdf

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

Adobe PDF - 105.5 KB - MD5: d5848f1f6416e7bdd398762644d454d1

Documentation

Experiment Instructions

TrautmannWakker_onlineappendix.pdf

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

Adobe PDF - 331.7 KB - MD5: 2b6021a539615f6772b733206204e5ce

Documentation

zTree_export.zip

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

ZIP Archive - 21.4 KB - MD5: df6a0e82e87934c193f2c581fefc5463

Code

zTree files (exported for long term preservation)

zTree.zip

Apr 18, 2018 - Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications [Dataset]

ZIP Archive - 19.4 KB - MD5: 5e4dea577d2674cd3a6b0af40c1f1860

Code

zTree files (original)

MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets

Apr 16, 2018 - GIScience and 3D Spatial Data Processing

Herfort, Benjamin, 2018, "MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets", doi:10.11588/data/3GYJUG, heiDATA, V1

MapSwipe is a mobile crowdsourcing application designed for smartphones and tablets to generate geographic information from satellite imagery. Data from 55 projects containing more than nine million tasks and more than 30 million individual classification results contributed by a...

global_datasets.zip

Apr 16, 2018 - MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets

ZIP Archive - 297.4 MB - MD5: 605e8b210f7a7e0dd8858f21bdb7d0de

Data

laos_datasets.zip

Apr 16, 2018 - MapSwipe: global dataset of crowdsourced classifications on human settlements and reference datasets

ZIP Archive - 138.8 MB - MD5: 54433b68ddd165b749baa3843a8ab58e

Data

Add Data

You need to Sign Up or Log In to create a dataverse or add a dataset.

Link Dataverse

Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.