Sift - Analyse Page: Difference between revisions
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Sift's Analyse page is the go to section to create meaningful analysis on your data. This page holds a group and workspace widget, the same as which is in the [[Sift - Explore Page#Group and Workspace Widget|Explore Page]]. There are 2 main widgets within the Analyse page: the PCA widget and the SPM widget. Both of these pages allow you to do different analysis on your data: PCA is used to decompose your data into a lower-dimensional version of your data, and extract meaning about how to variance occurs within the data, while SPM is used to apply statistical tests across the entirety of your data, instead of relying on their application on summary statistics. | Sift's Analyse page is the go to section to create meaningful analysis on your data. This page holds a group and workspace widget, the same as which is in the [[Sift - Explore Page#Group and Workspace Widget|Explore Page]]. There are 2 main widgets within the Analyse page: the PCA widget and the SPM widget. Both of these pages allow you to do different analysis on your data: PCA is used to decompose your data into a lower-dimensional version of your data, and extract meaning about how to variance occurs within the data, while SPM is used to apply statistical tests across the entirety of your data, instead of relying on their application on summary statistics. | ||
[[file:AnalysePage.png]] | |||
== Principal Component Analysis == | == Principal Component Analysis == | ||
The PCA page consists of 6 sub-pages related to PCA: '''Variance Explained, Loading Vector, Workspace Scores, Group Scores, Extreme Plot and PC Reconstruction''' | |||
== Statistical Parametric Mapping == | == Statistical Parametric Mapping == |
Revision as of 14:44, 19 March 2024
Language: | English • français • italiano • português • español |
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Sift's Analyse page is the go to section to create meaningful analysis on your data. This page holds a group and workspace widget, the same as which is in the Explore Page. There are 2 main widgets within the Analyse page: the PCA widget and the SPM widget. Both of these pages allow you to do different analysis on your data: PCA is used to decompose your data into a lower-dimensional version of your data, and extract meaning about how to variance occurs within the data, while SPM is used to apply statistical tests across the entirety of your data, instead of relying on their application on summary statistics.
Principal Component Analysis
The PCA page consists of 6 sub-pages related to PCA: Variance Explained, Loading Vector, Workspace Scores, Group Scores, Extreme Plot and PC Reconstruction