{"id":4207,"date":"2026-01-16T10:22:48","date_gmt":"2026-01-16T10:22:48","guid":{"rendered":"https:\/\/devserver.admin.uoc.gr\/damsl\/?page_id=4207"},"modified":"2026-01-16T10:25:14","modified_gmt":"2026-01-16T10:25:14","slug":"damsl-103-bayesian-statistics","status":"publish","type":"page","link":"https:\/\/mscs.uoc.gr\/damsl\/damsl-103-bayesian-statistics\/","title":{"rendered":"DAMSL-103 BAYESIAN Statistics"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"4207\" class=\"elementor elementor-4207\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-47e7b33 e-flex e-con-boxed e-con e-parent\" data-id=\"47e7b33\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-2c87900 e-con-full e-flex e-con e-child\" data-id=\"2c87900\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-63fb3b4 elementor-widget elementor-widget-text-editor\" data-id=\"63fb3b4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong style=\"font-size: 22px;\">Type<\/strong><\/p><p><strong style=\"font-size: 16px;\">Elective<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6ff4fab e-con-full e-flex e-con e-child\" data-id=\"6ff4fab\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cbbdc33 elementor-widget elementor-widget-text-editor\" data-id=\"cbbdc33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong style=\"font-size: 22px;\">Course Code<\/strong><\/p><p><strong style=\"font-size: 16px;\">DAMSL-103<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4728792 e-con-full e-flex e-con e-child\" data-id=\"4728792\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e4dd7f1 elementor-widget elementor-widget-text-editor\" data-id=\"e4dd7f1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong style=\"font-size: 22px;\">Teaching Semester<\/strong><\/p><p><strong style=\"font-size: 16px;\">C semester<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-74b417e e-con-full e-flex e-con e-child\" data-id=\"74b417e\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c4e7ca8 elementor-widget elementor-widget-text-editor\" data-id=\"c4e7ca8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong style=\"font-size: 22px;\">ECTS Credits<\/strong><\/p><p><strong style=\"font-size: 16px;\">10<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-aea9e47 e-flex e-con-boxed e-con e-parent\" data-id=\"aea9e47\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-ca881e9 e-grid e-con-full e-con e-child\" data-id=\"ca881e9\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-8169c04 elementor-widget elementor-widget-text-editor\" data-id=\"8169c04\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"et_pb_module et_pb_text et_pb_text_5_tb_body et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><div class=\"custom-field course-field \"><h6>Student Performance Evaluation<\/h6><p>Homework\/Lab Assignments, Final exam\/project<\/p><\/div><\/div><\/div><div class=\"et_pb_module et_pb_text et_pb_text_6_tb_body et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><div class=\"custom-field course-field \"><h6>Prerequisite Courses<\/h6><p>Calculus, Linear Algebra, Probabilities, Python Programming<\/p><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ca0c741 e-flex e-con-boxed e-con e-parent\" data-id=\"ca0c741\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-6f13111 e-grid e-con-full e-con e-child\" data-id=\"6f13111\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6361eff elementor-widget elementor-widget-text-editor\" data-id=\"6361eff\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div id=\"outcomes\" class=\"et_pb_module et_pb_text et_pb_text_1_tb_body et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><div class=\"custom-field course-main \"><h6><span style=\"text-decoration: underline;\">Syllabus<\/span><\/h6><ul><li>Belief, Probability and Exchangeability<\/li><li>One Parameter Models<\/li><li>Monte Carlo Approximation<\/li><li>The Normal Model<\/li><li>Gibbs Sampling<\/li><li>Multivariate Normal Model<\/li><li>Hierarchical Modeling<\/li><li>Linear Regression<\/li><li>Metropolis Hastings<\/li><li>Binomial and Poisson Regression<\/li><\/ul><\/div><\/div><\/div><div id=\"outcomes\" class=\"et_pb_module et_pb_text et_pb_text_2_tb_body et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><div class=\"custom-field course-main \">\u00a0<\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-caa1dca elementor-widget elementor-widget-text-editor\" data-id=\"caa1dca\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h6><span style=\"text-decoration: underline;\">Learning Outcomes<\/span><\/h6><div id=\"outcomes\" class=\"et_pb_module et_pb_text et_pb_text_2_tb_body et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><div class=\"custom-field course-main \"><p>Upon successful completion of this course students will be able to<\/p><ul><li>Compute Bayesian estimates for a wide variety of statistical models, using R software.<\/li><li>Knowledge of fundamental sampling algorithms for performing posterior inference based on alternative prior distributions.<\/li><li>Computer implementation using real and synthetic data.<\/li><li>Applied problem solving using Bayesian statistical methodologies.<\/li><\/ul><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-396be16 e-flex e-con-boxed e-con e-parent\" data-id=\"396be16\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-93f3c11 elementor-widget elementor-widget-spacer\" data-id=\"93f3c11\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Type Elective Course Code DAMSL-103 Teaching Semester C semester ECTS Credits 10 Student Performance Evaluation Homework\/Lab Assignments, Final exam\/project Prerequisite Courses Calculus, Linear Algebra, Probabilities, Python Programming Syllabus Belief, Probability and Exchangeability One Parameter Models Monte Carlo Approximation The Normal Model Gibbs Sampling Multivariate Normal Model Hierarchical Modeling Linear Regression Metropolis Hastings Binomial and Poisson Regression \u00a0 Learning Outcomes Upon successful completion of this course students will be able to Compute Bayesian estimates for a wide variety of statistical models, using R software. Knowledge of fundamental sampling algorithms for performing posterior inference based on alternative prior distributions. Computer implementation using real and synthetic data. Applied problem solving using Bayesian statistical methodologies.<\/p>\n","protected":false},"author":194,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-4207","page","type-page","status-publish","hentry","post-no-thumbnail"],"acf":[],"_links":{"self":[{"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/pages\/4207","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/users\/194"}],"replies":[{"embeddable":true,"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/comments?post=4207"}],"version-history":[{"count":4,"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/pages\/4207\/revisions"}],"predecessor-version":[{"id":4229,"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/pages\/4207\/revisions\/4229"}],"wp:attachment":[{"href":"https:\/\/mscs.uoc.gr\/damsl\/wp-json\/wp\/v2\/media?parent=4207"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}