{"id":215,"date":"2026-01-19T17:37:45","date_gmt":"2026-01-19T17:37:45","guid":{"rendered":"https:\/\/novametrica.com\/?page_id=215"},"modified":"2026-04-06T11:35:59","modified_gmt":"2026-04-06T11:35:59","slug":"service__data-analytics","status":"publish","type":"page","link":"https:\/\/novametrica.com\/index.php\/service__data-analytics\/","title":{"rendered":"Service__Data-Analytics"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"215\" class=\"elementor elementor-215\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7cbfa7d e-con-full e-flex e-con e-parent\" data-id=\"7cbfa7d\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-e965ea5 e-con-full e-flex e-con e-child\" data-id=\"e965ea5\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-77c04c1 e-con-full e-flex e-con e-child\" data-id=\"77c04c1\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-d2b5a35 e-con-full e-flex e-con e-child\" data-id=\"d2b5a35\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4bd7045 elementor-widget elementor-widget-heading\" data-id=\"4bd7045\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Quantitative research and data collection services<\/h1>\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-7a62460 e-con-full e-flex e-con e-child\" data-id=\"7a62460\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-46090bd e-con-full e-flex e-con e-child\" data-id=\"46090bd\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-ee07fc3 e-con-full e-flex e-con e-child\" data-id=\"ee07fc3\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f6a0eeb elementor-align-left elementor-widget elementor-widget-button\" data-id=\"f6a0eeb\" data-element_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=\"#getintouch\" target=\"_blank\">\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\">Get in touch<\/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>\n\t\t\t\t<\/div>\n\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-ea7c92d e-con-full e-flex e-con e-parent\" data-id=\"ea7c92d\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-38e4766 e-con-full e-flex e-con e-child\" data-id=\"38e4766\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-e8adb52 e-con-full e-flex e-con e-child\" data-id=\"e8adb52\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d2ca966 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"d2ca966\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<p class=\"elementor-heading-title elementor-size-default\">We design and implement both standardized and tailored methodological approaches to suit the needs of general populations as well as specific target groups, including minorities, migrants, refugees, LGBTQIA+ communities, and diasporic populations.<\/p>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4e67ff2 elementor-widget elementor-widget-image\" data-id=\"4e67ff2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1401\" height=\"2\" src=\"https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1.png\" class=\"attachment-full size-full wp-image-734\" alt=\"\" srcset=\"https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1.png 1401w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1-300x1.png 300w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1-1024x1.png 1024w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1-150x2.png 150w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641055-1-768x1.png 768w\" sizes=\"(max-width: 1401px) 100vw, 1401px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b1347f elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"7b1347f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<p class=\"elementor-heading-title elementor-size-default\">With the global cost of data collection increasing annually, our methodologies are continuously updated to integrate advances in technology. We specialize in transitioning data collection across modalities (e.g., face-to-face to online) while ensuring longitudinal trend integrity. Our global infrastructure enables high-quality data collection services worldwide. These services can be offered as stand-alone operations or as components of broader research engagements that include data analysis and comprehensive reporting.<\/p>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f41e5e6 elementor-widget elementor-widget-image\" data-id=\"f41e5e6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1401\" height=\"2\" src=\"https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1.png\" class=\"attachment-full size-full wp-image-735\" alt=\"\" srcset=\"https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1.png 1401w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1-300x1.png 300w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1-1024x1.png 1024w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1-150x2.png 150w, https:\/\/novametrica.com\/wp-content\/uploads\/2026\/02\/Container-3641057-1-768x1.png 768w\" sizes=\"(max-width: 1401px) 100vw, 1401px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c344d35 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"c344d35\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<p class=\"elementor-heading-title elementor-size-default\">Our team of quantitative researchers provides expert guidance in formulating hypotheses and aligning them with appropriate quantitative methodologies. We support clients through all stages of the research process\u2014from identifying and collecting suitable data to performing complex analyses on existing datasets. Our statistical capabilities span from basic inferential tests (e.g., t-tests) to advanced procedures, including Bayesian inference.<\/p>\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-8cc3f81 e-con-full e-flex e-con e-child\" data-id=\"8cc3f81\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d5cdf08 elementor-widget elementor-widget-heading\" data-id=\"d5cdf08\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span data-metadata=\"&lt;!--(figmeta)eyJmaWxlS2V5IjoiNHdnTTRRWnhUTFdMeEkyZUJxUDhacCIsInBhc3RlSUQiOjE5NDk4NTA0MzgsImRhdGFUeXBlIjoic2NlbmUifQo=(\/figmeta)--&gt;\"><\/span><span 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\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VWErhRkGYSu2HkgwgLU0akTsoV10YbUZ56LuDrLQujTLrJZjdIb+Nugk\/4aIWmi0\/h5S2t+KZnsh\/iUhYSms7YfldtJgKOfjY0G2Y7KCBq4XhJDsb4ClaEQFkWopJA6JS6OenQxnxPzutqrrak7MMisccPT5wz1esZCVJZYpLpyFR7eCzOvawn5UyQ2Y8un8mZw1ZOgdmFroNx1oTR9NeudKcluBtejEskwhC8R+z6kAeZohAi1BWNBbvN8e81I47SmuiPNUm1NrcUly0LnFGigJEOWpf1ukcbkI1j6ecTVKrJINpbJs9rtmLU\/uru1\/joQOHkWkD0IHV4frcAs0toUC5il4zUpV5HOQPK7imk7LU\/Ixs62EsZE8yr1mWFyTX2GiRC0SGOyGj9IqOhSyUNsCJFRSVgvUpFb2RA0CzkC1ZVagxyBQHy8RRqTA+BuDSGe5XKbgv+5zPUP7UdgKLXuA+F\/jkBVei7B7VJrdiDxFf5P5FOkic8fAV2SggS11iLaHPUZLrCG4BGiNAy3jkFORnVXbafsZdRjmW4UTeEyWX+dkXyVZLSKM5qzlwl5L1z1ea92SoNFqiunEtRO7aOxfNmK+EgYqzXFwxD\/E9xhEJN5Qn1mDOGOxHBIJ24svo9GbSpEL280G9tHHeZbiNvFFtFp4I4J46WFpHx8NpJLb7l9A4kqvGznc1HEVTJCMCakDDFWkFkd5mgeITI9SvbgdmaIPqwTobm9MeYbutSa0qxv1ClowfJ6uVhDvNsQWU0iO0RYTjRa4X\/maO1TIZ8h1QNw51lI3NMtovdMIP6uLonhFHQn+Q+HsClPCMTXQIiTzCoRrkd8GcT7+SyJuE25ZmJPqRkfIvYE1r8moHsl6o\/WJCZC9NPMU\/OEQPxjlvz3GHtCr+5PiLAcQoY4hupBtgLrweZsbJ6FEH5pEW5gVkO5LqlzqEwjQ9WTcvfTgQzjYaCWjhpZQvw1RPaxrOuRsJmBnGch\/hdZpCG4nKLk9EBbg2gRKmtg8FAVoTF5OnZW8hmqCi3F+nCifJLPZVqpl6FyjdL1MDKFVFcx+3PVyBGcjoXojWAyXs0TmnJ7VR3C\/Vz138M95tK34yGW6D67Ar\/lFGWuhbjbYBHSxbArCYeHxqcUNd9uU6U7qgb1wVH2fA3e2CjxxF24bEM6WELsw1qbJ554Vgfn\/1aQRTj9UfK6BCdtiC4c3poS5l2kl38g\/gP5JwmKE5rOLcCenpgtFhLlHotUpT9HiteXhrkqbQi9lCdZq85QN7LMElM3CC\/pjuqGPhE05bK46UAWqkw7COUV6r4BwjYFsJquvI3zZy2k9hqPt5G6BylGvTV1M45fx\/wEPi2yocq+TIfyqatuwlWTnyhDB0uI+ZgzxqsM5e7NdPIii+iZX135ijbhFlo7lgl8gOH9t66v\/synfhT1Z02zRfJIE37mwnhHw\/86yLdY740tn56sw0HUa3mxVXzaIlXpJUD7GGgmTR9VfI3c\/6OJ2k7OXxDDLjzlNI1vFhDFzTrogXwbQmoGZDdRtCE8VsPcarssQtn+jvosJmADNk\/VCWmioItCxizBXHoIaWhNd29uL4We7fPROaDl\/5JFjNGZ8avmWwnzGJxlYQwV4S0WTy2m3yJsiiKkMbkQ0\/rNtlLHSyqbIawB0kgZzcb2oD\/fQiSSFgnE70Qlq0kaiw39fr4UNWvjfGJuROr8vBch2miS0HuYOo4lqJ9ZG\/xGkkSSLwc4lflczEZOiZqbjVU2swRytK6SfbuC5Gao2zMhnMiEzKRUT+rZPZP2v08\/V3CgS7U3chjrj7EAn\/7yMMQiWhdWQg8zqQhaG0KyscsxPA5YrEvkciTGhvRy5yQOoduD4FTaqRPMh6hdZf0JUQBczarKTALYTUVmso0OthO+sxL8\/6Eu3hzjWsopDFCuUu2aIRZRiFZCEUlF0NoQEojvxfk4IJenQtRvV4VYlX5VAznIBiSjgsb8Fw==(\/figma)--&gt;\"><\/span>Our Services Include:<\/h2>\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-a0d3419 e-flex e-con-boxed e-con e-parent\" data-id=\"a0d3419\" 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\t\t<div class=\"elementor-element elementor-element-7bb56ac elementor-widget elementor-widget-heading\" data-id=\"7bb56ac\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data Collection<\/h2>\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-3a721e7 e-flex e-con-boxed e-con e-parent\" data-id=\"3a721e7\" 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-7f6ed4d e-con-full e-flex e-con e-child\" data-id=\"7f6ed4d\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-ad08bf9 e-con-full e-flex e-con e-child\" data-id=\"ad08bf9\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e822b6e elementor-widget elementor-widget-text-editor\" data-id=\"e822b6e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>Contextual understanding of local cultural and political environments<\/li><li>Questionnaire development tailored to target populations<\/li><li>Double translation of instruments to ensure linguistic and cultural equivalence<\/li><li>Development of sampling frames<\/li><li>Conducting interviews in local languages<\/li><li>Rigorous training of enumerators and supervisors<\/li><li>Creation of detailed training manuals<\/li><\/ul>\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-fd1eeb7 e-con-full e-flex e-con e-child\" data-id=\"fd1eeb7\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-772b498 e-con-full e-flex e-con e-child\" data-id=\"772b498\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d9bc34a elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"d9bc34a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>CImplementation of quality assurance protocols<\/li><li>Construction of statistical weights<\/li><li>Vetting and preprocessing of raw data<\/li><li>Reliability and validity assessments<\/li><li>Comparative evaluations of various data collection modalities (e.g., in-person, telephone, online)<\/li><li>Cost-sensitive strategies for data collection<\/li><\/ul>\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-07a2ab3 e-flex e-con-boxed e-con e-parent\" data-id=\"07a2ab3\" 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\t\t<div class=\"elementor-element elementor-element-ee1b193 elementor-widget elementor-widget-heading\" data-id=\"ee1b193\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Data Cleaning and Psychometric Analysis<\/h2>\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-b018276 e-flex e-con-boxed e-con e-parent\" data-id=\"b018276\" 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-baa2170 e-con-full e-flex e-con e-child\" data-id=\"baa2170\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-e72b19d e-con-full e-flex e-con e-child\" data-id=\"e72b19d\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cd215d2 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"cd215d2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>Reliability and validity diagnostics<\/li><li>Psychometric evaluation, including both Classical Test Theory and Item Response Theory<\/li><\/ul>\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-7b1c98a e-con-full e-flex e-con e-child\" data-id=\"7b1c98a\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-6c264fc e-con-full e-flex e-con e-child\" data-id=\"6c264fc\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-37e1a33 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"37e1a33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul><li>Exploratory and Confirmatory Factor Analysis<\/li><li>Detection and resolution of data quality issues<\/li><\/ul>\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-fd447fb e-flex e-con-boxed e-con e-parent\" data-id=\"fd447fb\" 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\t\t<div class=\"elementor-element elementor-element-d5ef62a elementor-widget elementor-widget-heading\" data-id=\"d5ef62a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Survey and Test Design<\/h2>\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-4537701 e-flex e-con-boxed e-con e-parent\" data-id=\"4537701\" 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-33ed8df e-con-full e-flex e-con e-child\" data-id=\"33ed8df\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-3049d88 e-con-full e-flex e-con e-child\" data-id=\"3049d88\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-609092c elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"609092c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>Designing custom surveys and assessment tools based on client needs<\/li><li>Developing theoretical constructs in disciplines such as sociology, education, psychology, and workforce development<\/li><li>Item generation and validation with alignment to constructs<\/li><li>Sampling frame design and stratification<\/li><\/ul>\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-ae8ce7f e-con-full e-flex e-con e-child\" data-id=\"ae8ce7f\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-84538a9 e-con-full e-flex e-con e-child\" data-id=\"84538a9\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e7029d9 elementor-widget__width-auto elementor-widget elementor-widget-text-editor\" data-id=\"e7029d9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>Construction and application of sampling weights<\/li><li>Pilot testing of instruments<\/li><li>Routine administration of surveys or assessments<\/li><li>Development of scoring protocols and statistical analysis procedures<\/li><\/ul>\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-f9080f8 e-flex e-con-boxed e-con e-parent\" data-id=\"f9080f8\" 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\t\t<div class=\"elementor-element elementor-element-d5c1abe elementor-widget elementor-widget-heading\" data-id=\"d5c1abe\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Statistical Analysis and Predictive Modeling<\/h2>\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-6f362f4 e-flex e-con-boxed e-con e-parent\" data-id=\"6f362f4\" 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-3aba559 e-con-full e-flex e-con e-child\" data-id=\"3aba559\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-cfba873 e-con-full e-flex e-con e-child\" data-id=\"cfba873\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9ee884d elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"9ee884d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li>Univariate and multivariate group comparisons<\/li><li>Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), and Multivariate ANOVA (MANOVA)<\/li><li>Predictive analytics and model development<\/li><\/ul>\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-6dbc317 e-con-full e-flex e-con e-child\" data-id=\"6dbc317\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-17fa672 e-con-full e-flex e-con e-child\" data-id=\"17fa672\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-57c6af6 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"57c6af6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul role=\"list\"><li><span style=\"font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, 'Noto Sans', sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';\">Bayesian inference and other advanced modeling techniques<\/span><\/li><li><span style=\"font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, 'Noto Sans', sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';\">Presentation and interpretation of results for practical application and stakeholder communication development<\/span><\/li><\/ul>\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-28de895 e-flex e-con-boxed e-con e-parent\" data-id=\"28de895\" data-element_type=\"container\" id=\"getintouch\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e4484f7 elementor-widget elementor-widget-heading\" data-id=\"e4484f7\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Let's discuss your project<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5b3dad4 elementor-button-align-stretch elementor-widget elementor-widget-form\" data-id=\"5b3dad4\" data-element_type=\"widget\" data-settings=\"{&quot;step_next_label&quot;:&quot;Next&quot;,&quot;step_previous_label&quot;:&quot;Previous&quot;,&quot;button_width&quot;:&quot;100&quot;,&quot;step_type&quot;:&quot;number_text&quot;,&quot;step_icon_shape&quot;:&quot;circle&quot;}\" data-widget_type=\"form.default\">\n\t\t\t\t\t\t\t<form class=\"elementor-form\" method=\"post\" name=\"New Form\" aria-label=\"New Form\">\n\t\t\t<input type=\"hidden\" name=\"post_id\" value=\"215\"\/>\n\t\t\t<input type=\"hidden\" name=\"form_id\" value=\"5b3dad4\"\/>\n\t\t\t<input type=\"hidden\" name=\"referer_title\" value=\"Service__Data-Analytics\" \/>\n\n\t\t\t\t\t\t\t<input type=\"hidden\" name=\"queried_id\" value=\"215\"\/>\n\t\t\t\n\t\t\t<div class=\"elementor-form-fields-wrapper elementor-labels-above\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-field-type-text elementor-field-group elementor-column elementor-field-group-name elementor-col-100\">\n\t\t\t\t\t\t\t\t\t\t\t\t<label for=\"form-field-name\" class=\"elementor-field-label\">\n\t\t\t\t\t\t\t\tName\t\t\t\t\t\t\t<\/label>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<input size=\"1\" type=\"text\" name=\"form_fields[name]\" id=\"form-field-name\" class=\"elementor-field elementor-size-md  elementor-field-textual\" placeholder=\"Name\">\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<div class=\"elementor-field-type-text elementor-field-group elementor-column elementor-field-group-field_2279bc4 elementor-col-100\">\n\t\t\t\t\t\t\t\t\t\t\t\t<label for=\"form-field-field_2279bc4\" class=\"elementor-field-label\">\n\t\t\t\t\t\t\t\tCompany Name\t\t\t\t\t\t\t<\/label>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<input size=\"1\" type=\"text\" name=\"form_fields[field_2279bc4]\" id=\"form-field-field_2279bc4\" class=\"elementor-field elementor-size-md  elementor-field-textual\" placeholder=\"LLC New\">\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<div class=\"elementor-field-type-email elementor-field-group elementor-column elementor-field-group-email elementor-col-100 elementor-field-required\">\n\t\t\t\t\t\t\t\t\t\t\t\t<label for=\"form-field-email\" class=\"elementor-field-label\">\n\t\t\t\t\t\t\t\tEmail\t\t\t\t\t\t\t<\/label>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<input size=\"1\" type=\"email\" name=\"form_fields[email]\" id=\"form-field-email\" class=\"elementor-field elementor-size-md  elementor-field-textual\" placeholder=\"Email\" required=\"required\">\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<div class=\"elementor-field-type-textarea elementor-field-group elementor-column elementor-field-group-message elementor-col-100\">\n\t\t\t\t\t\t\t\t\t\t\t\t<label for=\"form-field-message\" class=\"elementor-field-label\">\n\t\t\t\t\t\t\t\tMessage\t\t\t\t\t\t\t<\/label>\n\t\t\t\t\t\t<textarea class=\"elementor-field-textual elementor-field  elementor-size-md\" name=\"form_fields[message]\" id=\"form-field-message\" rows=\"4\" placeholder=\"Message\"><\/textarea>\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<div class=\"elementor-field-group elementor-column elementor-field-type-submit elementor-col-100 e-form__buttons\">\n\t\t\t\t\t<button class=\"elementor-button elementor-size-md\" type=\"submit\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Submit<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/button>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/form>\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>Quantitative research and data collection services Get in touch We design and implement both standardized and tailored methodological approaches to suit the needs of general populations as well as specific target groups, including minorities, migrants, refugees, LGBTQIA+ communities, and diasporic populations. With the global cost of data collection increasing annually, our methodologies are continuously updated [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-215","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/pages\/215","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/comments?post=215"}],"version-history":[{"count":109,"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/pages\/215\/revisions"}],"predecessor-version":[{"id":1098,"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/pages\/215\/revisions\/1098"}],"wp:attachment":[{"href":"https:\/\/novametrica.com\/index.php\/wp-json\/wp\/v2\/media?parent=215"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}