BESA Statistics
BESA Statistics provides optimized, user-guided workflows for cross-subject analysis of EEG / MEG data. The statistical method used is parameter-free permutation testing on the basis of Student’s t-tests (Maris, E. and Oostenveld, R., 2007). The program is maximally user-friendly. All analyses are computed automatically with user-interaction minimized to defining time and / or frequency ranges of interest. Statistical values computed in BESA Statistics can be directly used for scientific reports. No further analysis in other programs is needed. All results are visualized and can be directly used for publications.
BESA Statistics integrates optimally with data that were analyzed in BESA Research, but it can also process data from other software packages as long as they conform to the BESA Statistics file format.
BESA Statistics will automatically identify clusters in time, and if applicable frequency and space that show significant and stable differences between two groups or conditions. Results are corrected for multiple comparisons as only those data periods will be marked significant that survive the data re-shuffling of the permutation test. Thus, results obtained by BESA Statistics are objective and robust.
System requirements
- Windows® 7, Vista or XP Service Pack 2
- Processor: minimum: 2 GHz
- RAM: minimum: 2 GB
- Display resolution: minimum: 1280x800 pixels
- Graphics card supporting OpenGL 1.1 with 16 MB RAM or more
Certification
BESA is CE certified.
Click here to see the conformity declaration for BESA Statistics 1.0.
Price list
For inquiries on purchasing our products, please contact our sales office at: sales@besa.de.
Results of Permutation Test for ERF Data
Significant clusters are overlaid on a topographic map of the difference between groups / conditions or the corresponding t-values.
Significant Clusters are labeled
Channels belonging to the same cluster (ERP / ERF) are labeled by stars of the same color.
Summary of Cluster Significance
Clusters are automatically sorted for their significance.
Results of Permutation Test for Time-Frequency Data
Significant time-frequency periods are masked.