{"id":9779,"date":"2023-11-09T10:10:25","date_gmt":"2023-11-09T09:10:25","guid":{"rendered":"https:\/\/statistica.pro\/uncategorized\/modeler\/"},"modified":"2023-11-13T11:11:07","modified_gmt":"2023-11-13T10:11:07","slug":"modeler","status":"publish","type":"post","link":"https:\/\/statistica.pro\/en\/products\/modeler\/","title":{"rendered":"Modeler"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"9779\" class=\"elementor elementor-9779 elementor-98\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3f62de0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3f62de0\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8439ba2\" data-id=\"8439ba2\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-263e3d3 elementor-widget elementor-widget-text-editor\" data-id=\"263e3d3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Extensions to previous packages for quick and easy <\/span><b>analysis of large (big data) sets and the creation of predictive models <\/b><span style=\"font-weight: 400;\">using machine learning, AI and ETL.<\/span><\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p><span style=\"font-weight: 400;\">View Full Version <\/span><b>Modeler <\/b> <span style=\"font-weight: 400;\">use Statistica primarily for the analysis of large (big data) sets and for the creation of advanced predictive models. The package includes <\/span><b>a range of machine learning, AI and ETL tools<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The Modeler version will be used primarily by data scientists and analysts <\/span><b>for predicting and modelling the behaviour of variables under different conditions<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The application is available in desktop, network and server form.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9d33107 e-flex e-con-boxed e-con e-parent\" data-id=\"9d33107\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-1bdb694 e-flex e-con-boxed e-con e-child\" data-id=\"1bdb694\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-75a19be elementor-align-center elementor-widget elementor-widget-button\" data-id=\"75a19be\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/statistica.pro\/en\/trial-version\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Try it free for 30 days<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f290af3 elementor-widget elementor-widget-text-editor\" data-id=\"f290af3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><em>No need to enter payment details<\/em><\/p>\n\t\t\t\t\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-28ae375 e-flex e-con-boxed e-con e-child\" data-id=\"28ae375\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2c3f45e elementor-align-center elementor-widget elementor-widget-button\" data-id=\"2c3f45e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#analytickefunkce\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Overview of analytical functions<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-6eb214d e-flex e-con-boxed e-con e-parent\" data-id=\"6eb214d\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-caf83f1 e-flex e-con-boxed e-con e-child\" data-id=\"caf83f1\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-71be21a elementor-widget elementor-widget-heading\" data-id=\"71be21a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Import of data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ce4912 elementor-widget elementor-widget-text-editor\" data-id=\"2ce4912\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Modeler is fully compatible with xlsx (including xls), csv and fixed width data (e.g. in text files). It will allow you to:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>retrieve data from SQL, NoSQL and other databases<\/b><span style=\"font-weight: 400;\">,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">via integrated PI connector <\/span><b>retrieve data from OSIsoft PI system <\/b><span style=\"font-weight: 400;\">(a popular solution for operational data management),<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">import Spotfire SBDF data files,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>integrate two or more data sets <\/b><span style=\"font-weight: 400;\">into one graphical environment and a series of outputs.<\/span><\/li>\n<\/ul>\t\t\t\t\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-2c408ee e-flex e-con-boxed e-con e-child\" data-id=\"2c408ee\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-69a1408 elementor-widget elementor-widget-gallery\" data-id=\"69a1408\" data-element_type=\"widget\" data-e-type=\"widget\" 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href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/External-data.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"69a1408\" data-elementor-lightbox-title=\"External data\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4MSwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvRXh0ZXJuYWwtZGF0YS5wbmciLCJzbGlkZXNob3ciOiI2OWExNDA4In0%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/External-data.png\" data-width=\"482\" data-height=\"358\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Import-Excel.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"69a1408\" data-elementor-lightbox-title=\"Import Excel\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4NCwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvSW1wb3J0LUV4Y2VsLnBuZyIsInNsaWRlc2hvdyI6IjY5YTE0MDgifQ%3D%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Import-Excel-768x329.png\" data-width=\"768\" data-height=\"329\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-d5bbee4 e-flex e-con-boxed e-con e-parent\" data-id=\"d5bbee4\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-5b56aea e-flex e-con-boxed e-con e-child\" data-id=\"5b56aea\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ecf2aa8 elementor-widget elementor-widget-gallery\" data-id=\"ecf2aa8\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;columns&quot;:2,&quot;lazyload&quot;:&quot;yes&quot;,&quot;gallery_layout&quot;:&quot;grid&quot;,&quot;columns_tablet&quot;:2,&quot;columns_mobile&quot;:1,&quot;gap&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;link_to&quot;:&quot;file&quot;,&quot;aspect_ratio&quot;:&quot;3:2&quot;,&quot;overlay_background&quot;:&quot;yes&quot;,&quot;content_hover_animation&quot;:&quot;fade-in&quot;}\" data-widget_type=\"gallery.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-gallery__container\">\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_Health_Check.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"ecf2aa8\" data-elementor-lightbox-title=\"Data_Health_Check\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM5MiwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvRGF0YV9IZWFsdGhfQ2hlY2sucG5nIiwic2xpZGVzaG93IjoiZWNmMmFhOCJ9\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_Health_Check.png\" data-width=\"830\" data-height=\"324\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_Health_Check_setup.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"ecf2aa8\" data-elementor-lightbox-title=\"Data_Health_Check_setup\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM5MSwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvRGF0YV9IZWFsdGhfQ2hlY2tfc2V0dXAucG5nIiwic2xpZGVzaG93IjoiZWNmMmFhOCJ9\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_Health_Check_setup.png\" data-width=\"700\" data-height=\"522\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Import-Excel.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"ecf2aa8\" data-elementor-lightbox-title=\"Import Excel\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4NCwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvSW1wb3J0LUV4Y2VsLnBuZyIsInNsaWRlc2hvdyI6ImVjZjJhYTgifQ%3D%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Import-Excel.png\" data-width=\"910\" data-height=\"390\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_transformation.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"ecf2aa8\" data-elementor-lightbox-title=\"Data_transformation\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM3OSwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvRGF0YV90cmFuc2Zvcm1hdGlvbi5wbmciLCJzbGlkZXNob3ciOiJlY2YyYWE4In0%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Data_transformation-1024x495.png\" data-width=\"1024\" data-height=\"495\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\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-20de389 e-flex e-con-boxed e-con e-child\" data-id=\"20de389\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-006f562 elementor-widget elementor-widget-heading\" data-id=\"006f562\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data preparation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4d94aad elementor-widget elementor-widget-text-editor\" data-id=\"4d94aad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Modeler offers <\/span><b>automated data cleaning <\/b><span style=\"font-weight: 400;\">from duplicate, inconsistent and outlying values (or their recoding) using the so-called<\/span> <b><i>Data Health Check<\/i><\/b><span style=\"font-weight: 400;\"> (DHC) function.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For advanced data transformation, the tool <\/span><b><i>Rules Builder<\/i><\/b><span style=\"font-weight: 400;\">which allows you to process data from different sources according to complex rules (even using conditional expressions).<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For easier processing, bring your data closer to a normal layout by using the built-in <\/span><b>Box-Cox transformation<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-92aa15b e-flex e-con-boxed e-con e-parent\" data-id=\"92aa15b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-c18bfe3 e-flex e-con-boxed e-con e-child\" data-id=\"c18bfe3\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6ce8147 elementor-widget elementor-widget-heading\" data-id=\"6ce8147\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data evaluation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c268fcd elementor-widget elementor-widget-text-editor\" data-id=\"c268fcd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In the Modeler version, you can evaluate measured data (including big data files), among others using: <\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">classical methods <\/span><b>descriptive, parametric and non-parametric statistics<\/b><span style=\"font-weight: 400;\">,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">exploratory analysis and visualization,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>multivariate statistical methods <\/b><span style=\"font-weight: 400;\">for data organization and classification,<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">advanced linear and non-linear models,<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>estimation of many variance components and accuracy <\/b><span style=\"font-weight: 400;\">in the data sets (<\/span><i><span style=\"font-weight: 400;\">Variance Estimation and Precision<\/span><\/i><span style=\"font-weight: 400;\">).<\/span><\/li>\n<\/ul>\t\t\t\t\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-96b7827 e-flex e-con-boxed e-con e-child\" data-id=\"96b7827\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9b7547c elementor-widget elementor-widget-gallery\" data-id=\"9b7547c\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;gallery_layout&quot;:&quot;justified&quot;,&quot;lazyload&quot;:&quot;yes&quot;,&quot;ideal_row_height&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:200,&quot;sizes&quot;:[]},&quot;ideal_row_height_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:150,&quot;sizes&quot;:[]},&quot;ideal_row_height_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:150,&quot;sizes&quot;:[]},&quot;gap&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;link_to&quot;:&quot;file&quot;,&quot;overlay_background&quot;:&quot;yes&quot;,&quot;content_hover_animation&quot;:&quot;fade-in&quot;}\" data-widget_type=\"gallery.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-gallery__container\">\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Frequency_tables.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"9b7547c\" data-elementor-lightbox-title=\"Frequency_tables\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4MiwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvRnJlcXVlbmN5X3RhYmxlcy5wbmciLCJzbGlkZXNob3ciOiI5Yjc1NDdjIn0%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Frequency_tables.png\" data-width=\"786\" data-height=\"458\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Multivariate_analysis.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"9b7547c\" data-elementor-lightbox-title=\"Multivariate_analysis\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4NiwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvTXVsdGl2YXJpYXRlX2FuYWx5c2lzLnBuZyIsInNsaWRlc2hvdyI6IjliNzU0N2MifQ%3D%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Multivariate_analysis-1024x957.png\" data-width=\"1024\" data-height=\"957\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/ANOVA.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"9b7547c\" data-elementor-lightbox-title=\"ANOVA\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM3NSwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvQU5PVkEucG5nIiwic2xpZGVzaG93IjoiOWI3NTQ3YyJ9\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/ANOVA.png\" data-width=\"824\" data-height=\"588\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Parreto-chart.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"9b7547c\" data-elementor-lightbox-title=\"Parreto chart\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4NywidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvUGFycmV0by1jaGFydC5wbmciLCJzbGlkZXNob3ciOiI5Yjc1NDdjIn0%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Parreto-chart.png\" data-width=\"528\" data-height=\"342\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-56f3201 e-flex e-con-boxed e-con e-parent\" data-id=\"56f3201\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-b6b1e1f e-flex e-con-boxed e-con e-child\" data-id=\"b6b1e1f\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e924dad elementor-widget elementor-widget-image\" data-id=\"e924dad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"812\" height=\"682\" src=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Exponential_Smoothing_Forecastinh.png\" class=\"attachment-large size-large wp-image-9140\" alt=\"\" srcset=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Exponential_Smoothing_Forecastinh.png 812w, https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Exponential_Smoothing_Forecastinh-300x252.png 300w, https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Exponential_Smoothing_Forecastinh-768x645.png 768w\" sizes=\"(max-width: 812px) 100vw, 812px\" \/>\t\t\t\t\t\t\t\t\t\t\t\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-803806a e-flex e-con-boxed e-con e-child\" data-id=\"803806a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-36cf9ba elementor-widget elementor-widget-heading\" data-id=\"36cf9ba\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Predictive modelling<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-76d2898 elementor-widget elementor-widget-text-editor\" data-id=\"76d2898\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Use data mining, text mining and neural network tools to create <\/span><b>models of the behaviour of the observed variables in different situations<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The modern PMML language is used to generate them. Outputs can be further modified as required.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-f317716 e-flex e-con-boxed e-con e-parent\" data-id=\"f317716\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-d43a56a e-flex e-con-boxed e-con e-child\" data-id=\"d43a56a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-541b08e elementor-widget elementor-widget-heading\" data-id=\"541b08e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Other features<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-20d7ff4 elementor-widget elementor-widget-text-editor\" data-id=\"20d7ff4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Statistica in this version also offers the possibility to program <\/span><b>custom scripts in R, Python or C#<\/b><span style=\"font-weight: 400;\">. The modeler can also be used for e.g. for: <\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>understanding the key parameters affecting critical quality attributes <\/b><span style=\"font-weight: 400;\">(process analysis, quality control and multivariate statistical process control functions),<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>design of experiments <\/b><span style=\"font-weight: 400;\">and their virtual execution (design of experiments function &#8211; <\/span><i><span style=\"font-weight: 400;\">Design of Experiments<\/span><\/i><span style=\"font-weight: 400;\">, test power analysis &#8211; <\/span><i><span style=\"font-weight: 400;\">Power Analysis<\/span><\/i><span style=\"font-weight: 400;\"> and interval estimation &#8211; <\/span><i><span style=\"font-weight: 400;\">Interval Estimation<\/span><\/i><span style=\"font-weight: 400;\">).<\/span><\/li>\n<\/ul>\t\t\t\t\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-9e9d5dd e-flex e-con-boxed e-con e-child\" data-id=\"9e9d5dd\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-03d8885 elementor-widget elementor-widget-image\" data-id=\"03d8885\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"XR_Diagram\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6OTE1MCwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvWFJfRGlhZ3JhbS0xLnBuZyJ9\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"768\" height=\"577\" src=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1-768x577.png\" class=\"attachment-medium_large size-medium_large wp-image-9150\" alt=\"\" srcset=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1-768x577.png 768w, https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1-300x225.png 300w, https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1-1024x769.png 1024w, https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/XR_Diagram-1.png 1071w\" sizes=\"(max-width: 768px) 100vw, 768px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-94dc557 e-flex e-con-boxed e-con e-parent\" data-id=\"94dc557\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-8d26e3c e-flex e-con-boxed e-con e-child\" data-id=\"8d26e3c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-88275ef elementor-widget elementor-widget-gallery\" data-id=\"88275ef\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;gallery_layout&quot;:&quot;justified&quot;,&quot;lazyload&quot;:&quot;yes&quot;,&quot;ideal_row_height&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:200,&quot;sizes&quot;:[]},&quot;ideal_row_height_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:150,&quot;sizes&quot;:[]},&quot;ideal_row_height_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:150,&quot;sizes&quot;:[]},&quot;gap&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;gap_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:10,&quot;sizes&quot;:[]},&quot;link_to&quot;:&quot;file&quot;,&quot;overlay_background&quot;:&quot;yes&quot;,&quot;content_hover_animation&quot;:&quot;fade-in&quot;}\" data-widget_type=\"gallery.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-gallery__container\">\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Graphs.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"88275ef\" data-elementor-lightbox-title=\"Graphs\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4MywidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvR3JhcGhzLnBuZyIsInNsaWRlc2hvdyI6Ijg4Mjc1ZWYifQ%3D%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Graphs-1024x630.png\" data-width=\"1024\" data-height=\"630\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Box_plot.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"88275ef\" data-elementor-lightbox-title=\"Box_plot\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM3NywidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvQm94X3Bsb3QucG5nIiwic2xpZGVzaG93IjoiODgyNzVlZiJ9\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Box_plot.png\" data-width=\"568\" data-height=\"420\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Matrix_Plot.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"88275ef\" data-elementor-lightbox-title=\"Matrix_Plot\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM4NSwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvTWF0cml4X1Bsb3QucG5nIiwic2xpZGVzaG93IjoiODgyNzVlZiJ9\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Matrix_Plot.png\" data-width=\"552\" data-height=\"412\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t<a class=\"e-gallery-item elementor-gallery-item elementor-animated-content\" href=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Histogram_menu_dialog.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-slideshow=\"88275ef\" data-elementor-lightbox-title=\"Histogram_menu_dialog\" data-e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6NzM3NCwidXJsIjoiaHR0cHM6XC9cL3N0YXRpc3RpY2EucHJvXC93cC1jb250ZW50XC91cGxvYWRzXC8yMDE4XC8wNFwvSGlzdG9ncmFtX21lbnVfZGlhbG9nLnBuZyIsInNsaWRlc2hvdyI6Ijg4Mjc1ZWYifQ%3D%3D\">\n\t\t\t\t\t<div class=\"e-gallery-image elementor-gallery-item__image\" data-thumbnail=\"https:\/\/statistica.pro\/wp-content\/uploads\/2018\/04\/Histogram_menu_dialog.png\" data-width=\"572\" data-height=\"364\" aria-label=\"\" role=\"img\" ><\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-gallery-item__overlay\"><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\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-8ff31d4 e-flex e-con-boxed e-con e-child\" data-id=\"8ff31d4\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-87ad195 elementor-widget elementor-widget-heading\" data-id=\"87ad195\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Visualisation and outputs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-12ac1e3 elementor-widget elementor-widget-text-editor\" data-id=\"12ac1e3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In Modeler you can see the distribution of the acquired data and the results, among others in histogram, line, box, point, scatter and quantile plots and more  <\/span><b>frequently used 2D and 3D imaging methods<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The results obtained can <\/span><b>export <\/b> <span style=\"font-weight: 400;\">e.g. in the form of: <\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">\n<p><span style=\"font-weight: 400;\">simple and advanced reports,<\/span><\/p>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">\n<p><span style=\"font-weight: 400;\">entry into different types of databases,<\/span><\/p>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">\n<p><span style=\"font-weight: 400;\">MS Word (docx), MS Excel (xlsx) and text files (csv) or pdf.<\/span><\/p>\n<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\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\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div class=\"elementor-element elementor-element-b6d59f2 e-flex e-con-boxed e-con e-parent\" data-id=\"b6d59f2\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-94ac4ce elementor-widget elementor-widget-toggle\" data-id=\"94ac4ce\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"toggle.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle-item\">\n\t\t\t\t\t<h3 id=\"elementor-tab-title-1551\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-1551\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon elementor-toggle-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon-closed\"><i class=\"fas fa-caret-right\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon-opened\"><i class=\"elementor-toggle-icon-opened fas fa-caret-up\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-toggle-title\" tabindex=\"0\">Overview of analytical functions<\/a>\n\t\t\t\t\t<\/h3>\n\n\t\t\t\t\t<div id=\"elementor-tab-content-1551\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-1551\"><ul>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/statistica-anova-manova\"><span data-contrast=\"none\">ANOVA\/MANOVA<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-association-rules\"><span data-contrast=\"none\">Association Rules<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-automated-neural-networks\"><span data-contrast=\"none\">Automated Neural Networks<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-boosted-tree\"><span data-contrast=\"none\">Boosted Tree<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-calculators\"><span data-contrast=\"none\">Calculators; Distributions, Pearson Product Moment Correlation Coefficient, Six Sigma<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-canonical-analysis\"><span data-contrast=\"none\">Canonical Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-classification-trees\"><span data-contrast=\"none\">Classification Trees<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-cluster-analysis\"><span data-contrast=\"none\">Cluster Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-correlation\"><span data-contrast=\"none\">Correlation<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-correspondence-analysis\"><span data-contrast=\"none\">Correspondence Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-cox-proportional-hazards-models\"><span data-contrast=\"none\">Cox Proportional Hazards Models<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Data Miner Recipes<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-descriptive-statistics\"><span data-contrast=\"none\">Descriptive Statistics<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-design-experiments\"><span data-contrast=\"none\">Design of Experiments (DOE)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-discriminant-function-analysis\"><span data-contrast=\"none\">Discriminant Function Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-distribution-fitting\"><span data-contrast=\"none\">Distribution Fitting<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-distributions-simulation\"><span data-contrast=\"none\">Distributions &amp; Simulation<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/statistica-dynamic-time-warping\"><span data-contrast=\"none\">Dynamic Time Warping<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-extract-transform-and-load\"><span data-contrast=\"none\">Extract, Transform, and Load<\/span><\/a><span data-contrast=\"none\">(analytics are used to align time based data)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statisticatm-factor-analysis\"><span data-contrast=\"none\">Factor Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Faster Independent Component Analysis<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Feature Selection<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-fixed-nonlinear-regression\"><span data-contrast=\"none\">Fixed Nonlinear Regression<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">General CHAID Models<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">General Classification and Regression Trees (C&amp;RT)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-general-discriminant-analysis\"><span data-contrast=\"none\">General Discriminant Analysis (GDA)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-general-linear-models\"><span data-contrast=\"none\">General Linear Models (GLM)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-general-partial-least-squares-models\"><span data-contrast=\"none\">General Partial Least Squares Models (PLS)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-general-regression-models\"><span data-contrast=\"none\">General Regression Models (GRM)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Generalized Additive Models (GAM)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-generalized-linear-nonlinear-models\"><span data-contrast=\"none\">Generalized Linear\/Nonlinear Models (GLZ)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Goodness of Fit, Classification, Prediction<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Independent Component Analysis<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Interactive Tree (C&amp;RT, CHAID)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Lasso Regression<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Link Analysis<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-log-linear-analysis-frequency-tables\"><span data-contrast=\"none\">Log-Linear Analysis of Frequency Tables<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Machine Learning (Bayesian, Support Vectors, K-Nearest)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-multidimensional-scaling\"><span data-contrast=\"none\">Multidimensional Scaling (MDS)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Multivariate Adaptive Regression Splines (MARSplines)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-multiple-regression\"><span data-contrast=\"none\">Multiple Regression<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-nonlinear-estimation\"><span data-contrast=\"none\">Nonlinear Estimation<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-nonparametric-statistics\"><span data-contrast=\"none\">Nonparametric Statistics<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-power-analysis-and-interval-estimation\"><span data-contrast=\"none\">Power Analysis and Interval Estimation<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-multivariate-statistical-process-control\"><span data-contrast=\"none\">Multivariate Statistical Process Control (MSPC &#8211; PCA\/PLS)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Optimal Binning<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Predictor Screening<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-principal-components-classification-analysis\"><span data-contrast=\"none\">Principal Components &amp; Classification Analysis (PCCA)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-process-analysis\"><span data-contrast=\"none\">Process Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-quality-control-charts\"><span data-contrast=\"none\">Quality Control Charts<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Random Forests<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Rapid Deployment of Predictive Models (PMML)<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-reliability-and-item-analysis\"><span data-contrast=\"none\">Reliability and Item Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Sequence and Link Analysis<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-stepwise-model-builder\"><span data-contrast=\"none\">Stepwise Model Builder (what-if)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-structural-equation-modeling-and-path-analysis\"><span data-contrast=\"none\">Structural Equation Modeling and Path Analysis (SEPATH)<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-survival-failure-time-analysis\"><span data-contrast=\"none\">Survival &amp; Failure Time Analysis<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-time-series-forecasting\"><span data-contrast=\"none\">Time series \/ forecasting<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-t-tests-and-other-tests-group-differences\"><span data-contrast=\"none\">t-tests and other tests of group differences<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-tabulate\"><span data-contrast=\"none\">Tabulate<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><a href=\"https:\/\/community.tibco.com\/wiki\/tibco-statistica-variance-components-mixed-model-anova\"><span data-contrast=\"none\">Variance Components &amp; Mixed Model ANOVA\/ANCOVA<\/span><\/a><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<li><span data-contrast=\"none\">Weight of Evidence<\/span><span data-ccp-props=\"{\"201341983\":0,\"335559739\":160,\"335559740\":240}\"> <\/span><\/li>\n<\/ul>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\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>Extensions to previous packages for quick and easy analysis of large (big data) sets and the creation of predictive models using machine learning, AI and&#8230;<\/p>\n","protected":false},"author":2,"featured_media":8993,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kadence_starter_templates_imported_post":false,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[46],"tags":[],"class_list":["post-9779","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-products"],"_links":{"self":[{"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/posts\/9779","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/comments?post=9779"}],"version-history":[{"count":0,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/posts\/9779\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/media\/8993"}],"wp:attachment":[{"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/media?parent=9779"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/categories?post=9779"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statistica.pro\/en\/wp-json\/wp\/v2\/tags?post=9779"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}