{"action":"opened","issue":{"url":"https://api.github.com/repos/mne-tools/mne-python/issues/2191","labels_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2191/labels{/name}","comments_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2191/comments","events_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2191/events","html_url":"https://github.com/mne-tools/mne-python/issues/2191","id":85834365,"number":2191,"title":"ENH: tutorials / special doc needed","user":{"login":"dengemann","id":1908618,"avatar_url":"https://avatars.githubusercontent.com/u/1908618?v=3","gravatar_id":"","url":"https://api.github.com/users/dengemann","html_url":"https://github.com/dengemann","followers_url":"https://api.github.com/users/dengemann/followers","following_url":"https://api.github.com/users/dengemann/following{/other_user}","gists_url":"https://api.github.com/users/dengemann/gists{/gist_id}","starred_url":"https://api.github.com/users/dengemann/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dengemann/subscriptions","organizations_url":"https://api.github.com/users/dengemann/orgs","repos_url":"https://api.github.com/users/dengemann/repos","events_url":"https://api.github.com/users/dengemann/events{/privacy}","received_events_url":"https://api.github.com/users/dengemann/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-06-07T01:39:41Z","updated_at":"2015-06-07T01:39:41Z","closed_at":null,"body":"We should have a few extended docs/ tutorials, maybe in the FAQ section on at least the following topics:\r\n\r\n- epochs selection and event handling (see #1963)\r\n- artefact removal\r\n- group statistics (make explicit 2 (spatial /  no spatial prior) X 2 (F/T-test) API, clarify TFCE (it's not another test, but an enhancement method)), clarify that despite t-test inputs, spatio-temporal permutation clustering is not parametric and alos it does not give a multiple comparison corrected t-map, which means it's not just a thresholding to a parametric stat. Also add recent insights on decoding stats. Discuss repeated measure designs and options (hierarchial subtraction with t-test, rANOVA, etc.)\r\n- ...\r\n\r\ncc @wmvanvliet @kingjr @mainakjas @jona-sassenhagen @teonlamont "}}