[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_toggle title=”Description” open_toggle_text_color=”#000000″ open_toggle_background_color=”#FFFFFF” closed_toggle_text_color=”#000000″ closed_toggle_background_color=”#e9ac2c” icon_color=”#24781a” toggle_icon=”P||divi||400″ open_icon_color=”#24781a” open_toggle_icon=”O||divi||400″ _builder_version=”4.27.4″ _module_preset=”default” title_text_color=”#000000″ border_radii=”on|20px|20px|20px|20px” locked=”off” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n In these lectures we cover some of the techniques in data analysis which have been developed in a cosmological context. We start by considering the general problem of estimating parameters from data, focusing on Monte Carlo Markov Chains (MCMC) for small catalogs. Then, we continue with the Fisher matrix formalism to analyse experimental setups before any data are taken. In fact, the Fisher matrix formalism can be of great help to test the requirements of an experiment in order to reach the desired accuracy on the final parameters that need to be tested. All the codes shown during the lectures are in Python (preferred) and in Mathematica.<\/p>\n [\/et_pb_toggle][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” locked=”off” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.27.4″ _module_preset=”default” locked=”off” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”1_2″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" ADVANCED STATISTICS, FROM FISHER MATRIX TO MCMCs: Domenico Sapone [Chile U.] IFT UAM\/CSIC Blue Room | Red Room Time Blue Room: 15:00-17:00 | Red Room: 15:00-17:00 Dates Blue Room: October 7 2024 | Red Room: October 8,9 2024 In these lectures we cover some of the techniques in data analysis which have been developed in […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":2046,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-2051","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/pages\/2051","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/comments?post=2051"}],"version-history":[{"count":3,"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/pages\/2051\/revisions"}],"predecessor-version":[{"id":2056,"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/pages\/2051\/revisions\/2056"}],"up":[{"embeddable":true,"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/pages\/2046"}],"wp:attachment":[{"href":"https:\/\/projects.ift.uam-csic.es\/doctorado\/wp-json\/wp\/v2\/media?parent=2051"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/s.w.org\/images\/core\/emoji\/16.0.1\/svg\/1f4cd.svg\")
\nIFT UAM\/CSIC<\/b>
\nBlue Room | Red Room<\/p>\n<\/div>\n![\"\"](\"https:\/\/s.w.org\/images\/core\/emoji\/16.0.1\/svg\/23f0.svg\")
\nTime<\/b>
\nBlue Room:<\/b> 15:00-17:00 | Red Room:<\/b> 15:00-17:00<\/p>\n<\/div>\n![\"\"](\"https:\/\/s.w.org\/images\/core\/emoji\/16.0.1\/svg\/1f5d3.svg\")
\nDates<\/b>
\nBlue Room:<\/b> October 7 2024 | Red Room:<\/b> October 8,9 2024<\/p>\n<\/div>\n
\nWe consider different experimental setups and in each topic will face the built-in of the numerical codes alongside with the theoretical recipes in order to properly construct the observables.
\nThe last lecture will have a hands-on approach: the participants will choose the desired observable and will write their own code in their favored language.<\/p>\n\n
Participants<\/h3>\n
\n
\n