{"id":4385,"date":"2026-05-25T10:30:18","date_gmt":"2026-05-25T08:30:18","guid":{"rendered":"https:\/\/ellistat.com\/?p=4385"},"modified":"2026-05-27T10:32:05","modified_gmt":"2026-05-27T08:32:05","slug":"comparar-las-distribuciones-cramer-von-mises-test-y-energy-test","status":"publish","type":"post","link":"https:\/\/ellistat.com\/es\/comparer-des-distributions-test-de-cramer-von-mises-et-test-energie\/","title":{"rendered":"Comparaci\u00f3n de distribuciones: prueba de Cram\u00e9r-von Mises y prueba de la energ\u00eda"},"content":{"rendered":"

Comparar distribuciones en lugar de medias: un avance clave para el control de calidad gracias a las pruebas de Cram\u00e9e-von Mises y Energy<\/h2>\n\n\n\n

Dos lotes de piezas. La misma media. Misma desviaci\u00f3n t\u00edpica aparente. <\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

Los promedios y las varianzas son pr\u00e1cticamente id\u00e9nticos, aunque intuitivamente se percibe una diferencia entre las dos m\u00e1quinas.<\/p>\n\n\n\n

Sin embargo, las pruebas de hip\u00f3tesis convencionales no muestran diferencias entre ambas distribuciones.<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

Pero la media y la varianza s\u00f3lo cuentan una parte de la historia de un proceso de mecanizado. Para detectar diferencias reales entre grupos de mediciones, entre dos proveedores, dos m\u00e1quinas, dos equipos, dos periodos de producci\u00f3n... hay que comparar las distribuciones completas. Esto es precisamente lo que hacen dos pruebas estad\u00edsticas integradas en An\u00e1lisis de datos Ellistat<\/a> prueba: el Cram\u00e9r-von Mises<\/a> y la prueba de Energ\u00eda.<\/p>\n\n\n\n

La prueba Cram\u00e9r-von Mises<\/h2>\n\n\n\n

Esta prueba compara :<\/p>\n\n\n\n

    \n
  • o bien una muestra con una distribuci\u00f3n te\u00f3rica<\/li>\n\n\n\n
  • o dos muestras entre ellos<\/li>\n<\/ul>\n\n\n\n

    El principio:<\/strong> la prueba compara las funciones de distribuci\u00f3n acumulativa (ogives) de las dos distribuciones.<\/p>\n\n\n\n

    En otras palabras, \u00bfmide \u00ablo separadas que est\u00e1n las curvas acumulativas\u00bb?<\/p>\n\n\n\n

    Si las dos distribuciones est\u00e1n pr\u00f3ximas, las ojivas se solapan. Si difieren, aumenta la diferencia acumulada.<\/p>\n\n\n

    \n
    \"\"<\/figure>\n<\/div>\n\n\n

    La prueba energ\u00e9tica<\/h2>\n\n\n\n

    Esta prueba generaliza este enfoque a varios grupos. Resulta especialmente adecuado cuando :<\/p>\n\n\n\n

      \n
    • se comparan m\u00e1s de dos poblaciones<\/li>\n\n\n\n
    • las distribuciones son desconocidas<\/li>\n\n\n\n
    • los datos son multidimensionales<\/li>\n<\/ul>\n\n\n\n

      El principio <\/strong>La prueba se basa en una idea intuitiva: comparar distancias entre puntos.<\/p>\n\n\n\n

      Mide :<\/p>\n\n\n\n

        \n
      • distancias medias dentro de los grupos<\/li>\n\n\n\n
      • entonces las distancias entre grupos <\/li>\n<\/ul>\n\n\n\n

        Si los grupos proceden de la misma distribuci\u00f3n, las distancias intragrupo e intergrupo son similares. En caso contrario, las distancias entre grupos son mayores.<\/p>\n\n\n\n

        Qu\u00e9 significa esto en la pr\u00e1ctica<\/h2>\n\n\n\n

        Comparar dos proveedores en un di\u00e1metro cr\u00edtico. Validar un cambio de reglaje de la m\u00e1quina. Analizar un antes\/despu\u00e9s en un proceso inestable. Diferenciar dos centros de mecanizado que producen las mismas piezas... en apariencia.<\/p>\n\n\n\n

        En todos estos casos, fijarse \u00fanicamente en la media y la varianza puede inducir a error.<\/p>\n\n\n\n

        La comparaci\u00f3n de distribuciones completas ofrece una imagen real de lo que est\u00e1 ocurriendo.<\/p>\n\n\n\n

        En el m\u00f3dulo de an\u00e1lisis de datos de Ellistat, estas pruebas van acompa\u00f1adas de visualizaciones: ogives, KDE, histogramas superpuestos, porque un valor p sin contexto visual no convence a nadie en el taller.<\/p>\n\n\n\n

        \"\"<\/figure>\n\n\n\n

        El objetivo no es obtener un resultado estad\u00edstico, sino comprender por qu\u00e9 dos procesos se comportan de forma diferente y tomar medidas.<\/p>","protected":false},"excerpt":{"rendered":"

        Comparer les distributions plut\u00f4t que les moyennes : une avanc\u00e9e cl\u00e9 pour le contr\u00f4le qualit\u00e9 gr\u00e2ce aux test de Cram\u00e9e-von Mises et test Energie Deux lots de pi\u00e8ces. M\u00eame moyenne. M\u00eame \u00e9cart-type apparent. Les moyennes et les variances sont ici sensiblement identiques, et pourtant, intuitivement, on peut sentir une diff\u00e9rence entre ces deux machines. Les […]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[7],"tags":[],"class_list":["post-4385","post","type-post","status-publish","format-standard","hentry","category-data-analysis"],"acf":[],"yoast_head":"\nComparer des distributions : Test de Cram\u00e9r\u2013von Mises et test Energie - Ellistat<\/title>\n<meta name=\"description\" content=\"Moyenne identique, qualit\u00e9 diff\u00e9rente : d\u00e9couvrez pourquoi comparer les distributions compl\u00e8tes est plus fiable que la moyenne ou la variance.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ellistat.com\/es\/comparar-las-distribuciones-cramer-von-mises-test-y-energy-test\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Comparer des distributions : Test de Cram\u00e9r\u2013von Mises et test Energie - 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