[{"data":1,"prerenderedAt":1667},["Reactive",2],{"options:asyncdata:$ogpPUTwkW6:/p/puntuacion-directa:0":3},{"page":4,"book":26,"news":1661,"questionSent":19,"questions":1662,"formData":1663,"attachments":23,"chartData":23,"pending":19,"chartOptions":1664,"afspec":19,"aflink":1666},{"id":5,"book_id":6,"chapter_id":7,"name":8,"slug":9,"html":10,"priority":11,"created_at":12,"updated_at":13,"created_by":14,"updated_by":18,"draft":19,"markdown":20,"revision_count":21,"template":19,"owned_by":22,"editor":20,"trends":23,"raw_html":24,"tags":25},4105,2,0,"Puntuación directa","puntuacion-directa","\u003Cp id=\"bkmrk-la-puntuaci%C3%B3n-direct\">La \u003Cstrong>puntuación directa \u003C/strong>es el valor observado y medido en un elemento de una población respecto de una magnitud, de forma inmediata y sin ningún tipo de transformación. Por sí misma, una puntuación directa no indica si un valor es alto o bajo, requiriéndose para ello su comparación con la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/media-aritmetica-simple\">media\u003C/a>\u003C/strong> y la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/desviacion-tipica-desviacion-estandar\">desviación típica\u003C/a>\u003C/strong>, mediante la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/puntuacion-diferencial\">puntuación diferencial\u003C/a>\u003C/strong> y la\u003Cstrong> \u003Ca href=\"https://ikusmira.org/p/puntuacion-estandar-puntuacion-tipificada-valor-z\">puntuación típica\u003C/a>\u003C/strong> respectivamente. \u003C/p>",333,"2026-03-12T07:21:48.000000Z","2026-03-12T08:04:41.000000Z",{"id":15,"name":16,"slug":17},1,"Admin","admin",{"id":15,"name":16,"slug":17},false,"",3,{"id":15,"name":16,"slug":17},null,"\u003Cp id=\"bkmrk-la-puntuaci%C3%B3n-direct\">La \u003Cstrong>puntuación directa \u003C/strong>es el valor observado y medido en un elemento de una población respecto de una magnitud, de forma inmediata y sin ningún tipo de transformación. Por sí misma, una puntuación directa no indica si un valor es alto o bajo, requiriéndose para ello su comparación con la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/media-aritmetica-simple\">media\u003C/a>\u003C/strong> y la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/desviacion-tipica-desviacion-estandar\">desviación típica\u003C/a>\u003C/strong>, mediante la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/puntuacion-diferencial\">puntuación diferencial\u003C/a>\u003C/strong> y la\u003Cstrong> \u003Ca href=\"https://ikusmira.org/p/puntuacion-estandar-puntuacion-tipificada-valor-z\">puntuación típica\u003C/a>\u003C/strong> respectivamente. \u003C/p>",[],{"id":6,"name":27,"slug":28,"description":20,"created_at":29,"updated_at":30,"created_by":15,"updated_by":15,"owned_by":15,"default_template_id":23,"pages":31,"index":62,"shelves":1654},"Estadística general","estadistica-general","2023-05-06T08:26:42.000000Z","2023-05-16T06:24:05.000000Z",[32,37,42,47,52,57],{"id":33,"name":34,"slug":35,"html":36},3895,"Índice de discriminación (teoría de los tests)","indice-de-discriminacion-teoria-de-los-tests","\u003Cp id=\"bkmrk-en-teor%C3%ADa-de-los-tes\">En teoría de los tests y en relación a \u003Ca href=\"https://ikusmira.org/p/pruebas-de-ejecucion-maxima\">pruebas de ejecución máxima\u003C/a>, el \u003Cstrong>índice de discriminación\u003C/strong> es un \u003Ca href=\"https://ikusmira.org/p/estadigrafos\">estadígrafo\u003C/a> o coeficiente estadístico que mide la capacidad que desarrolla un ítem concreto para discriminar a aquellos sujetos con puntuación total alta de aquellos sujetos con puntuación total baja. Un índice de discriminación alto redunda en un mayor \u003Ca href=\"https://ikusmira.org/p/consistencia-interna\">consistencia interna\u003C/a> del test. \u003C/p>\r\n\u003Cp id=\"bkmrk-para-calcular-el-%C3%ADnd\">Para calcular el índice de discriminación se seleccionan el 27% de los sujetos con una menor puntación total , por un lado, y el 27% de los sujetos con una mayor puntuación, por otro; una vez seleccionados esos grupos, se calcula la resta entre la proporción de sujetos que han contestado correctamente en el grupo de puntuación superior y la proporción  de sujetos con respuesta correcta en el grupo de puntuación inferior. De esta forma, el índice de discriminación toma valores entre entre -1 y 1,  interpretándose los valores cercanos a 1 como ítems con gran capacidad de discriminación. \u003Cbr>\u003C/p>",{"id":38,"name":39,"slug":40,"html":41},2648,"Coeficiente de correlación biserial puntual","coeficiente-de-correlacion-biserial-puntual","\u003Cp id=\"bkmrk-el-coeficiente-de-co\">El \u003Cstrong>coeficiente de correlación biserial puntual o coeficiente de correlación punto-biserial\u003C/strong> es un coeficiente que mide la correlación o relación estadística entre una variable cuantitativa y una variable dicotómica genuina o pura, esto es, que no ha sido el objeto de una dicotomización artificial. Un ejemplo de esta situación es la correlación entre el sexo (variable dicotómica pura) y la calificación obtenida en un examen de matemáticas. Aunque el coeficiente de correlación biserial puntual coincide con el coeficiente de correlación lineal de Pearson cuando en este último la variable dicotómica se ha codificado en términos de 0s y 1s, lo habitual es referise a dicho coeficiente a través de esta fórmula:\u003C/p>\r\n\u003Cp id=\"bkmrk-%24%24r_%7Bbp%7D%3D%5Ccfrac%7B%5Cove\">$$r_{bp}=\\cfrac{\\overline{x}_p-\\overline{x}_q}{s_x}\\sqrt{pq}$$\u003C/p>\r\n\u003Cp id=\"bkmrk-donde-%5C%28%5Coverline%7Bx%7D\">donde \\(\\overline{x}_p\\) y \\(\\overline{x}_q\\) son las medias artméticas simples de las puntuaciones de la variable cuantitativa para cada grupo de la variable dicotómica (en el ejemplo del párrafo anterior, serían las medias de las calificaciones de los hombres, por un lado; y de las mujeres, por otro), \\(s_x\\) es la desviación típica de la variable cuantitativa, reuniendo los datos de los grupos (en el ejemplo, la desviación típica de todas las calificaciones, sin distinguir si corresponden a un hombre o una mujer), y \\(p\\) y \\(q\\) son las proporciones de elementos en cada grupo sobre el tamaño total de la muestra (en el ejemplo, proporción de hombres y proporción de mujeres).\u003C/p>\r\n\u003Cp id=\"bkmrk-al-igual-que-el-coef\">Al igual que el coeficiente de correlación de Pearson, el coeficiente de correlación biserial puntual toma valores en el intervalo [-1,1] y se interpreta del mismo modo que aquel, siendo la correlación mas intensa según nos acercamos en valor absoluto  al valor 1, mientras que el signo indica que grupo de la variable dicotómica obtiene mayores puntuaciones en la variable cuantitativa.\u003C/p>",{"id":43,"name":44,"slug":45,"html":46},309,"Media condicionada","media-condicionada","\u003Cp id=\"bkmrk-en-una-distribuci%C3%B3n-\">En una distribución conjunta de varias variables estadísitca, una \u003Cstrong>media condicionada\u003C/strong> es la media que toma los valores de una variable para un valor dado de otra variable. Por ejemplo, si disponemos de los datos de altura y perso para un grupo de personas; una media condicionada seria la media del peso para las personas con una altura inferior a 160cm (condicionada a que la altura es inferior a 160cm).\u003C/p>",{"id":48,"name":49,"slug":50,"html":51},2075,"Estadística bayesiana (inferencia bayesiana)","estadistica-bayesiana-inferencia-bayesiana","\u003Cp id=\"bkmrk-la-estad%C3%ADstica-bayes\">La \u003Cstrong>estadística bayesiana y más concretamente la inferencia bayesiana \u003C/strong>es un conjunto de métodos estadísticos que en base al teorema de Bayes, realiza estimaciones actualizadas de las distribuciones de probabilidad de parámetros desconocidos a partir probabilidades subjetivas iniciales relativas a ellos, en base a la evidencia proporcionada por los datos.\u003C/p>",{"id":53,"name":54,"slug":55,"html":56},2708,"Casos particulares","casos-particulares","\u003Cp id=\"bkmrk-los-casos-particular\">Los \u003Cstrong>casos particulares\u003C/strong> son las observaciones o datos individuales, tomados de uno en uno, que se recogen en una investigación estadísitica. Los casos particulares no representan pos sí mismo el feńómeno del cual son extraídos, y por tanto su consideración nunca debe ser en términos de tendenccia o pauta relacionada con dicho fenómeno. Únicamente a través de la consideración del conjunto de los casos particulares, a través de la \u003Cstrong>\u003Ca href=\"https://ikusmira.org/p/generalizacion-estadistica\">generalización estadística\u003C/a>\u003C/strong>, puede llegarse a entender las características globales del fenómeno a estudio. \u003C/p>",{"id":58,"name":59,"slug":60,"html":61},103,"Muestra invitada","muestra-invitada","\u003Cp id=\"bkmrk-la-muestra-invitada-\">La \u003Cstrong>muestra invitada\u003C/strong> es el conjunto de individuos a los que se ha invitado a participar en una encuesta, entrevista o experimento. La muestra de individuos invitados que aceptan formalmente participar se denomina muestra aceptante.\u003C/p>",{"":63},[64,68,72,76,80,85,90,95,100,105,110,112,117,122,127,132,137,142,147,149,154,159,164,169,174,179,184,189,194,199,204,209,214,219,224,229,233,238,242,247,252,257,262,267,271,275,280,285,290,295,299,304,309,314,319,324,329,334,339,344,349,354,359,364,369,374,379,384,389,394,399,404,409,414,418,423,428,433,438,443,448,453,458,462,467,472,476,481,486,491,496,498,503,508,513,518,522,527,532,537,542,547,552,557,561,566,571,576,581,586,591,596,601,606,611,616,621,626,631,636,641,646,651,656,661,666,671,676,681,686,691,696,701,706,711,716,721,726,731,736,741,746,751,755,759,764,769,773,777,781,786,791,796,798,802,807,812,817,822,827,832,837,841,846,851,856,861,866,871,876,881,886,891,895,900,905,910,915,920,925,930,935,940,944,949,951,956,961,966,971,976,980,985,990,995,1000,1004,1009,1014,1018,1023,1028,1033,1037,1042,1047,1052,1057,1061,1066,1071,1076,1081,1086,1091,1096,1101,1106,1110,1115,1120,1125,1129,1134,1139,1144,1148,1152,1157,1162,1167,1172,1177,1181,1185,1190,1195,1200,1205,1209,1214,1219,1222,1226,1231,1236,1240,1245,1250,1255,1260,1265,1270,1275,1280,1285,1290,1295,1300,1304,1309,1314,1319,1324,1329,1334,1339,1344,1349,1354,1359,1364,1369,1374,1379,1382,1386,1391,1396,1401,1405,1409,1413,1418,1422,1426,1431,1436,1441,1446,1451,1456,1461,1466,1471,1476,1481,1486,1491,1495,1500,1505,1509,1514,1519,1524,1529,1533,1537,1541,1546,1551,1556,1561,1566,1571,1576,1578,1583,1588,1593,1598,1603,1608,1613,1618,1623,1628,1633,1638,1643,1648,1653],{"id":65,"name":66,"slug":67,"priority":7,"chapter_name":23},3173,"Aleatorización (diseño de experimentos)","aleatorizacion-diseno-de-experimentos",{"id":69,"name":70,"slug":71,"priority":15,"chapter_name":23},631,"Amplitud de clase","amplitud-de-clase",{"id":73,"name":74,"slug":75,"priority":6,"chapter_name":23},387,"Análisis de trayectorias","analisis-de-trayectorias",{"id":77,"name":78,"slug":79,"priority":21,"chapter_name":23},624,"Arranque aleatorio","arranque-aleatorio",{"id":81,"name":82,"slug":83,"priority":84,"chapter_name":23},43,"Asociación estadística","asociacion-estadistica",4,{"id":86,"name":87,"slug":88,"priority":89,"chapter_name":23},2019,"Asociación no estadística","asociacion-no-estadistica",5,{"id":91,"name":92,"slug":93,"priority":94,"chapter_name":23},2948,"Banco de datos","banco-de-datos",6,{"id":96,"name":97,"slug":98,"priority":99,"chapter_name":23},1621,"Base del índice (periodo base)","base-del-indice-periodo-base",7,{"id":101,"name":102,"slug":103,"priority":104,"chapter_name":23},35,"Cálculo de la moda estadística para datos agrupados en intervalos","calculo-de-la-moda-estadistica-para-datos-agrupados-en-intervalos",8,{"id":106,"name":107,"slug":108,"priority":109,"chapter_name":23},3063,"Característica cualitativa","caracteristica-cualitativa",9,{"id":53,"name":54,"slug":55,"priority":111,"chapter_name":23},10,{"id":113,"name":114,"slug":115,"priority":116,"chapter_name":23},2730,"Censo estadístico","censo-estadistico",11,{"id":118,"name":119,"slug":120,"priority":121,"chapter_name":23},2551,"Clase mediana","clase-mediana",12,{"id":123,"name":124,"slug":125,"priority":126,"chapter_name":23},1011,"Clase modal","clase-modal",13,{"id":128,"name":129,"slug":130,"priority":131,"chapter_name":23},2133,"Coeficiente de asimetría de Bowley","coeficiente-de-asimetria-de-bowley",14,{"id":133,"name":134,"slug":135,"priority":136,"chapter_name":23},1714,"Coeficiente de asimetría de Fisher","coeficiente-de-asimetria-de-fisher",15,{"id":138,"name":139,"slug":140,"priority":141,"chapter_name":23},1844,"Coeficiente de asimetría de Pearson","coeficiente-de-asimetria-de-pearson",16,{"id":143,"name":144,"slug":145,"priority":146,"chapter_name":23},2057,"Coeficiente de contingencia de Pearson","coeficiente-de-contingencia-de-pearson",17,{"id":38,"name":39,"slug":40,"priority":148,"chapter_name":23},18,{"id":150,"name":151,"slug":152,"priority":153,"chapter_name":23},1938,"Coeficiente de curtosis de Pearson","coeficiente-de-curtosis-de-pearson",19,{"id":155,"name":156,"slug":157,"priority":158,"chapter_name":23},2032,"Coeficiente de determinación ajustado (coeficiente de determinación corregido)","coeficiente-de-determinacion-ajustado-coeficiente-de-determinacion-corregido",20,{"id":160,"name":161,"slug":162,"priority":163,"chapter_name":23},2649,"Coeficiente de Tschuprow","coeficiente-de-tschuprow",21,{"id":165,"name":166,"slug":167,"priority":168,"chapter_name":23},37,"Coeficiente de variación","coeficiente-de-variacion",22,{"id":170,"name":171,"slug":172,"priority":173,"chapter_name":23},2646,"Coeficiente Q de Yule","coeficiente-q-de-yule",23,{"id":175,"name":176,"slug":177,"priority":178,"chapter_name":23},2218,"Comprobación de Charlier","comprobacion-de-charlier",24,{"id":180,"name":181,"slug":182,"priority":183,"chapter_name":23},2095,"Concepto de estadística","concepto-de-estadistica",25,{"id":185,"name":186,"slug":187,"priority":188,"chapter_name":23},2607,"Constante estadística","constante-estadistica",26,{"id":190,"name":191,"slug":192,"priority":193,"chapter_name":23},2087,"Corrección de Bessel","correccion-de-bessel",27,{"id":195,"name":196,"slug":197,"priority":198,"chapter_name":23},308,"Corrección de Sheppard","correccion-de-sheppard",28,{"id":200,"name":201,"slug":202,"priority":203,"chapter_name":23},1080,"Corrección de Yates","correccion-de-yates",29,{"id":205,"name":206,"slug":207,"priority":208,"chapter_name":23},49,"Corrección por continuidad","correccion-por-continuidad",30,{"id":210,"name":211,"slug":212,"priority":213,"chapter_name":23},2685,"Correlación","correlacion",31,{"id":215,"name":216,"slug":217,"priority":218,"chapter_name":23},1624,"Correlación espuria (correlación espúrea)","correlacion-espuria-correlacion-espurea",32,{"id":220,"name":221,"slug":222,"priority":223,"chapter_name":23},2684,"Correlación por rangos","correlacion-por-rangos",33,{"id":225,"name":226,"slug":227,"priority":228,"chapter_name":23},1665,"Correlograma","correlograma",34,{"id":230,"name":231,"slug":232,"priority":101,"chapter_name":23},148,"Covariación","covariacion",{"id":234,"name":235,"slug":236,"priority":237,"chapter_name":23},44,"Covarianza","covarianza",36,{"id":239,"name":240,"slug":241,"priority":165,"chapter_name":23},1652,"Criterio (variable)","criterio-variable",{"id":243,"name":244,"slug":245,"priority":246,"chapter_name":23},2135,"Cuartiles (primer cuartil, segundo cuartil, tercer cuartil)","cuartiles-primer-cuartil-segundo-cuartil-tercer-cuartil",38,{"id":248,"name":249,"slug":250,"priority":251,"chapter_name":23},2159,"Cuasivarianza (varianza corregida)","cuasivarianza-varianza-corregida",39,{"id":253,"name":254,"slug":255,"priority":256,"chapter_name":23},1669,"Curtosis (estadística)","curtosis-estadistica",40,{"id":258,"name":259,"slug":260,"priority":261,"chapter_name":23},2072,"Datos agregados","datos-agregados",41,{"id":263,"name":264,"slug":265,"priority":266,"chapter_name":23},1732,"Datos agrupados","datos-agrupados",42,{"id":268,"name":269,"slug":270,"priority":81,"chapter_name":23},2692,"Datos aislados (datos no agrupados)","datos-aislados-datos-no-agrupados",{"id":272,"name":273,"slug":274,"priority":234,"chapter_name":23},2745,"Datos bivariados","datos-bivariados",{"id":276,"name":277,"slug":278,"priority":279,"chapter_name":23},73,"Datos blandos","datos-blandos",45,{"id":281,"name":282,"slug":283,"priority":284,"chapter_name":23},2315,"Datos cualitativos","datos-cualitativos",46,{"id":286,"name":287,"slug":288,"priority":289,"chapter_name":23},2900,"Datos desagregados","datos-desagregados",47,{"id":291,"name":292,"slug":293,"priority":294,"chapter_name":23},241,"Datos estructurados y datos no estructurados","datos-estructurados-y-datos-no-estructurados",48,{"id":296,"name":297,"slug":298,"priority":205,"chapter_name":23},2726,"Datos no agrupados","datos-no-agrupados",{"id":300,"name":301,"slug":302,"priority":303,"chapter_name":23},2038,"Deciles","deciles",50,{"id":305,"name":306,"slug":307,"priority":308,"chapter_name":23},142,"Desigualdad de Markov","desigualdad-de-markov",51,{"id":310,"name":311,"slug":312,"priority":313,"chapter_name":23},1609,"Desviación media absoluta","desviacion-media-absoluta",52,{"id":315,"name":316,"slug":317,"priority":318,"chapter_name":23},1923,"Desviación típica (desviación estándar)","desviacion-tipica-desviacion-estandar",53,{"id":320,"name":321,"slug":322,"priority":323,"chapter_name":23},2055,"Diagrama de barras (gráfico de columnas)","diagrama-de-barras-grafico-de-columnas",54,{"id":325,"name":326,"slug":327,"priority":328,"chapter_name":23},2945,"Diagrama de caja y bigotes","diagrama-de-caja-y-bigotes",55,{"id":330,"name":331,"slug":332,"priority":333,"chapter_name":23},2765,"Diagrama de frecuencias","diagrama-de-frecuencias",56,{"id":335,"name":336,"slug":337,"priority":338,"chapter_name":23},1854,"Diagrama de sectores (gráfico circular)","diagrama-de-sectores-grafico-circular",57,{"id":340,"name":341,"slug":342,"priority":343,"chapter_name":23},2066,"Diagrama de tallo y hojas","diagrama-de-tallo-y-hojas",58,{"id":345,"name":346,"slug":347,"priority":348,"chapter_name":23},775,"Diseño experimental","diseno-experimental",59,{"id":350,"name":351,"slug":352,"priority":353,"chapter_name":23},279,"Distribución asimétrica negativa (a la izquierda)","distribucion-asimetrica-negativa-a-la-izquierda",60,{"id":355,"name":356,"slug":357,"priority":358,"chapter_name":23},3180,"Distribución asimétrica positiva (a la derecha)","distribucion-asimetrica-positiva-a-la-derecha",61,{"id":360,"name":361,"slug":362,"priority":363,"chapter_name":23},3172,"Distribución bimodal","distribucion-bimodal",62,{"id":365,"name":366,"slug":367,"priority":368,"chapter_name":23},307,"Distribución bivariada","distribucion-bivariada",63,{"id":370,"name":371,"slug":372,"priority":373,"chapter_name":23},795,"Distribución conjunta","distribucion-conjunta",64,{"id":375,"name":376,"slug":377,"priority":378,"chapter_name":23},1702,"Distribución de frecuencias","distribucion-de-frecuencias",65,{"id":380,"name":381,"slug":382,"priority":383,"chapter_name":23},2634,"Distribución de frecuencias acumuladas","distribucion-de-frecuencias-acumuladas",66,{"id":385,"name":386,"slug":387,"priority":388,"chapter_name":23},1693,"Distribución de frecuencias agrupada 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