264:@0.031627:0.974518:0.062330:0.974518:0.062330:0.956333:0.031627:0.956333:0.000000:0.000000:0.000000
Estadística y probabilidad:@0.073089:0.043661:0.304737:0.043661:0.304737:0.024916:0.073089:0.024916:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
4.2 Regresión lineal simple. Método de mínimos cuadrados:@0.293660:0.136836:0.755979:0.136836:0.755979:0.119889:0.293660:0.119889:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
En el análisis de la regresión lineal simple, a las dos variables involucradas las asignamos :@0.293660:0.163491:0.931341:0.163491:0.931341:0.147778:0.293660:0.147778:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
con “ ” y “ ”. A la variable   se le denomina variable independiente, mientras que a la :@0.293660:0.180133:0.930768:0.180133:0.930768:0.164420:0.293660:0.164420:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
x:@0.330898:0.180133:0.338353:0.180133:0.338353:0.163727:0.330898:0.163727:0.000000
y:@0.364510:0.180133:0.371983:0.180133:0.371983:0.163727:0.364510:0.163727:0.000000
x:@0.480825:0.180133:0.488280:0.180133:0.488280:0.163727:0.480825:0.163727:0.000000
variable y se la llama variable dependiente. El análisis de la regresión se utiliza, por :@0.293660:0.196775:0.931230:0.196775:0.931230:0.181062:0.293660:0.181062:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
ejemplo, para construir una función dependiente de una o más constantes por :@0.293660:0.213416:0.930987:0.213416:0.930987:0.197704:0.293660:0.197704:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
determinar, a la que denominamos modelo matemático de predicción, en cuyo caso   :@0.293660:0.230058:0.930938:0.230058:0.930938:0.214346:0.293660:0.214346:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
x:@0.919452:0.230058:0.926906:0.230058:0.926906:0.213652:0.919452:0.213652:0.000000
se denomina variable de predicción, mientras que y se llama variable de respuesta.:@0.293660:0.246700:0.891850:0.246700:0.891850:0.230987:0.293660:0.230987:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
En el análisis de la regresión, la variable   puede considerarse ordinaria, esto es, no se :@0.293660:0.281204:0.930824:0.281204:0.930824:0.265491:0.293660:0.265491:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
x:@0.589906:0.281204:0.597361:0.281204:0.597361:0.264798:0.589906:0.264798:0.000000
trata de una variable aleatoria. Por su parte, la variable   es una variable aleatoria, y se :@0.293679:0.297846:0.930971:0.297846:0.930971:0.282133:0.293679:0.282133:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
y:@0.699025:0.297846:0.706498:0.297846:0.706498:0.281440:0.699025:0.281440:0.000000
supone que la media   depende de la variable independiente  .:@0.293660:0.314488:0.754081:0.314488:0.754081:0.298775:0.293660:0.298775:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
y:@0.450711:0.314488:0.458184:0.314488:0.458184:0.298082:0.450711:0.298082:0.000000
y:@0.743478:0.314488:0.750952:0.314488:0.750952:0.298082:0.743478:0.298082:0.000000
Construimos una función que tiene la forma de un polinomio de grado  1 cuya gráfica :@0.293642:0.348992:0.930986:0.348992:0.930986:0.333279:0.293642:0.333279:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
≤:@0.812377:0.349574:0.827710:0.349574:0.827710:0.331920:0.812377:0.331920:0.000000
se identifica con la de una recta. Con mayor precisión, se considera el problema siguiente: :@0.293642:0.365634:0.931162:0.365634:0.931162:0.349921:0.293642:0.349921:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
halla un polinomio p de grado  1 de la forma::@0.293642:0.382276:0.631163:0.382276:0.631163:0.366563:0.293642:0.366563:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
≤:@0.518081:0.382858:0.533415:0.382858:0.533415:0.365204:0.518081:0.365204:0.000000
y p x:@0.513903:0.416780:0.563639:0.416780:0.563639:0.400374:0.513903:0.400374:0.000000:0.000000:0.000000:0.000000:0.000000
= ( )= +:@0.522407:0.417362:0.613781:0.417362:0.613781:0.399708:0.522407:0.399708:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a bx,    x:@0.588158:0.416780:0.671579:0.416780:0.671579:0.400374:0.588158:0.400374:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
∀ ∊ℝ:@0.650834:0.417362:0.702246:0.417362:0.702246:0.399708:0.650834:0.399708:0.000000:0.000000:0.000000:0.000000
,:@0.703258:0.416780:0.706590:0.416780:0.706590:0.400374:0.703258:0.400374:0.000000
donde  , :@0.293605:0.451284:0.361362:0.451284:0.361362:0.435571:0.293605:0.435571:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a b:@0.345108:0.451284:0.370105:0.451284:0.370105:0.434878:0.345108:0.434878:0.000000:0.000000:0.000000
∊ℝ:@0.369995:0.451866:0.399575:0.451866:0.399575:0.434212:0.369995:0.434212:0.000000:0.000000
 son calculados con el denominado método de mínimos cuadrados, cuyo :@0.400551:0.451284:0.930564:0.451284:0.930564:0.435571:0.400551:0.435571:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
algoritmo se describe a continuación. :@0.293605:0.467926:0.570102:0.467926:0.570102:0.452213:0.293605:0.452213:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
4.3 Algoritmo:@0.293605:0.503442:0.401598:0.503442:0.401598:0.486495:0.293605:0.486495:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Para calcular las constantes óptimas :@0.293605:0.530097:0.556483:0.530097:0.556483:0.514384:0.293605:0.514384:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a, b:@0.556074:0.530013:0.581016:0.530013:0.581016:0.513607:0.556074:0.513607:0.000000:0.000000:0.000000:0.000000
 mediante el método de mínimos cuadrados, se :@0.581488:0.530113:0.931170:0.530113:0.931170:0.514400:0.581488:0.514400:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
requiere la siguiente información::@0.293653:0.546755:0.535987:0.546755:0.535987:0.531042:0.293653:0.531042:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
1. :@0.293660:0.581265:0.309730:0.581265:0.309730:0.565553:0.293660:0.565553:0.000000:0.000000:0.000000
El número de puntos :@0.353907:0.581265:0.510748:0.581265:0.510748:0.565553:0.353907:0.565553:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
n:@0.510536:0.581265:0.520034:0.581265:0.520034:0.564859:0.510536:0.564859:0.000000
≥:@0.519961:0.581848:0.535294:0.581848:0.535294:0.564193:0.519961:0.564193:0.000000
2.:@0.535202:0.581265:0.547314:0.581265:0.547314:0.565553:0.535202:0.565553:0.000000:0.000000
2. :@0.293660:0.615777:0.309730:0.615777:0.309730:0.600064:0.293660:0.600064:0.000000:0.000000:0.000000
El conjunto de datos :@0.353907:0.615777:0.507398:0.615777:0.507398:0.600064:0.353907:0.600064:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
S:@0.507179:0.615777:0.515242:0.615777:0.515242:0.599371:0.507179:0.599371:0.000000
={(:@0.515168:0.616359:0.542576:0.616359:0.542576:0.598705:0.515168:0.598705:0.000000:0.000000:0.000000
x y:@0.542484:0.615777:0.570576:0.615777:0.570576:0.599371:0.542484:0.599371:0.000000:0.000000:0.000000
i:@0.549881:0.618949:0.552124:0.618949:0.552124:0.609789:0.549881:0.609789:0.000000
 , :@0.552076:0.615777:0.563194:0.615777:0.563194:0.600064:0.552076:0.600064:0.000000:0.000000:0.000000
i:@0.570507:0.618949:0.572750:0.618949:0.572750:0.609789:0.570507:0.609789:0.000000
) ∊ ℝ:@0.572702:0.616359:0.616475:0.616359:0.616475:0.598705:0.572702:0.598705:0.000000:0.000000:0.000000:0.000000:0.000000
2:@0.616199:0.609713:0.621436:0.609713:0.621436:0.600552:0.616199:0.600552:0.000000
 | :@0.621390:0.615777:0.633207:0.615777:0.633207:0.600064:0.621390:0.600064:0.000000:0.000000:0.000000
i:@0.633115:0.615777:0.636907:0.615777:0.636907:0.599371:0.633115:0.599371:0.000000
=:@0.636833:0.616359:0.652166:0.616359:0.652166:0.598705:0.636833:0.598705:0.000000
1, …,  .:@0.652074:0.615777:0.712119:0.615777:0.712119:0.600064:0.652074:0.600064:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
n:@0.693454:0.615777:0.702952:0.615777:0.702952:0.599371:0.693454:0.599371:0.000000
}:@0.702878:0.616359:0.709008:0.616359:0.709008:0.598705:0.702878:0.598705:0.000000
4.4 Aplicación del método de mínimos cuadrados:@0.293648:0.651293:0.681132:0.651293:0.681132:0.634346:0.293648:0.634346:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
1. :@0.293660:0.677944:0.309730:0.677944:0.309730:0.662232:0.293660:0.662232:0.000000:0.000000:0.000000
Calcula las siguientes sumas::@0.353907:0.677944:0.560626:0.677944:0.560626:0.662232:0.353907:0.662232:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
S:@0.477204:0.718225:0.485266:0.718225:0.485266:0.701819:0.477204:0.701819:0.000000
1:@0.485199:0.721397:0.490436:0.721397:0.490436:0.712237:0.485199:0.712237:0.000000
=:@0.490390:0.718807:0.505723:0.718807:0.505723:0.701153:0.490390:0.701153:0.000000
i:@0.510729:0.725052:0.512797:0.725052:0.512797:0.716103:0.510729:0.716103:0.000000
=:@0.512757:0.725370:0.521120:0.725370:0.521120:0.715740:0.512757:0.715740:0.000000
1:@0.521070:0.725052:0.525970:0.725052:0.525970:0.716481:0.521070:0.716481:0.000000
x:@0.528691:0.711693:0.532757:0.711693:0.532757:0.702744:0.528691:0.702744:0.000000
i:@0.532723:0.713420:0.533947:0.713420:0.533947:0.708423:0.532723:0.708423:0.000000
n:@0.515760:0.702684:0.520941:0.702684:0.520941:0.693735:0.515760:0.693735:0.000000
Σ:@0.509979:0.721159:0.526721:0.721159:0.526721:0.697085:0.509979:0.697085:0.000000
, :@0.533999:0.718225:0.541159:0.718225:0.541159:0.702512:0.533999:0.702512:0.000000:0.000000
S:@0.541067:0.718225:0.549129:0.718225:0.549129:0.701819:0.541067:0.701819:0.000000
2:@0.549069:0.721397:0.554306:0.721397:0.554306:0.712237:0.549069:0.712237:0.000000
=:@0.554258:0.718807:0.569592:0.718807:0.569592:0.701153:0.554258:0.701153:0.000000
i:@0.574597:0.725052:0.576665:0.725052:0.576665:0.716103:0.574597:0.716103:0.000000
=:@0.576625:0.725370:0.584988:0.725370:0.584988:0.715740:0.576625:0.715740:0.000000
1:@0.584938:0.725052:0.589838:0.725052:0.589838:0.716481:0.584938:0.716481:0.000000
x:@0.592559:0.711693:0.596625:0.711693:0.596625:0.702744:0.592559:0.702744:0.000000
i:@0.596592:0.713420:0.597815:0.713420:0.597815:0.708423:0.596592:0.708423:0.000000
2:@0.597792:0.708383:0.600648:0.708383:0.600648:0.703387:0.597792:0.703387:0.000000
n:@0.579629:0.702684:0.584809:0.702684:0.584809:0.693735:0.579629:0.693735:0.000000
Σ:@0.573849:0.721159:0.590591:0.721159:0.590591:0.697085:0.573849:0.697085:0.000000
, :@0.601264:0.718225:0.608424:0.718225:0.608424:0.702512:0.601264:0.702512:0.000000:0.000000
R:@0.608332:0.718225:0.617278:0.718225:0.617278:0.701819:0.608332:0.701819:0.000000
1:@0.617216:0.721397:0.622453:0.721397:0.622453:0.712237:0.617216:0.712237:0.000000
=:@0.622407:0.718807:0.637740:0.718807:0.637740:0.701153:0.622407:0.701153:0.000000
i:@0.642745:0.725052:0.644814:0.725052:0.644814:0.716103:0.642745:0.716103:0.000000
=:@0.644773:0.725370:0.653137:0.725370:0.653137:0.715740:0.644773:0.715740:0.000000
1:@0.653087:0.725052:0.657987:0.725052:0.657987:0.716481:0.653087:0.716481:0.000000
y:@0.660707:0.711693:0.664784:0.711693:0.664784:0.702744:0.660707:0.702744:0.000000
i:@0.664750:0.713420:0.665974:0.713420:0.665974:0.708423:0.664750:0.708423:0.000000
n:@0.647777:0.702684:0.652958:0.702684:0.652958:0.693735:0.647777:0.693735:0.000000
Σ:@0.641997:0.721159:0.658740:0.721159:0.658740:0.697085:0.641997:0.697085:0.000000
, :@0.667751:0.718225:0.674911:0.718225:0.674911:0.702512:0.667751:0.702512:0.000000:0.000000
R:@0.674819:0.718225:0.683765:0.718225:0.683765:0.701819:0.674819:0.701819:0.000000
2:@0.683703:0.721397:0.688940:0.721397:0.688940:0.712237:0.683703:0.712237:0.000000
=:@0.688894:0.718807:0.704227:0.718807:0.704227:0.701153:0.688894:0.701153:0.000000
i:@0.709232:0.725052:0.711301:0.725052:0.711301:0.716103:0.709232:0.716103:0.000000
=:@0.711260:0.725370:0.719624:0.725370:0.719624:0.715740:0.711260:0.715740:0.000000
1:@0.719574:0.725052:0.724474:0.725052:0.724474:0.716481:0.719574:0.716481:0.000000
x y:@0.727194:0.711693:0.738661:0.711689:0.738661:0.702741:0.727194:0.702744:0.000000:0.000000:0.000000
i:@0.731227:0.713420:0.732451:0.713420:0.732451:0.708423:0.731227:0.708423:0.000000
 :@0.732425:0.711689:0.734624:0.711689:0.734624:0.703119:0.732425:0.703119:0.000000
i:@0.738620:0.713420:0.739844:0.713420:0.739844:0.708423:0.738620:0.708423:0.000000
n:@0.714264:0.702684:0.719445:0.702684:0.719445:0.693735:0.714264:0.693735:0.000000
Σ:@0.708484:0.721159:0.725227:0.721159:0.725227:0.697085:0.708484:0.697085:0.000000
.:@0.740165:0.718225:0.743368:0.718225:0.743368:0.702512:0.740165:0.702512:0.000000
2.:@0.293660:0.752735:0.305772:0.752735:0.305772:0.737023:0.293660:0.737023:0.000000:0.000000
Verifica:@0.353907:0.752735:0.405766:0.752735:0.405766:0.737023:0.353907:0.737023:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
z n:@0.409668:0.752735:0.443776:0.752735:0.443776:0.736329:0.409668:0.736329:0.000000:0.000000:0.000000
=:@0.417933:0.753318:0.433266:0.753318:0.433266:0.735664:0.417933:0.735664:0.000000
S S:@0.444807:0.752735:0.478978:0.752735:0.478978:0.737023:0.444807:0.737023:0.000000:0.000000:0.000000
2:@0.454387:0.755908:0.459624:0.755908:0.459624:0.746747:0.454387:0.746747:0.000000
–:@0.460221:0.753318:0.469424:0.753318:0.469424:0.735664:0.460221:0.735664:0.000000
1:@0.480002:0.755908:0.485239:0.755908:0.485239:0.746747:0.480002:0.746747:0.000000
2:@0.485840:0.746674:0.491077:0.746674:0.491077:0.737514:0.485840:0.737514:0.000000
≠:@0.491669:0.753318:0.507002:0.753318:0.507002:0.735664:0.491669:0.735664:0.000000
0.:@0.508014:0.752735:0.521231:0.752735:0.521231:0.737023:0.508014:0.737023:0.000000:0.000000
3. :@0.293660:0.787246:0.309730:0.787246:0.309730:0.771533:0.293660:0.771533:0.000000:0.000000:0.000000
Calcula la constante óptima de regresión lineal  ::@0.353907:0.787246:0.709463:0.787246:0.709463:0.771533:0.353907:0.771533:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a:@0.695793:0.787166:0.705052:0.787166:0.705052:0.770760:0.695793:0.770760:0.000000
a:@0.553867:0.832622:0.563126:0.832622:0.563126:0.816216:0.553867:0.816216:0.000000
=:@0.565442:0.833281:0.580775:0.833281:0.580775:0.815626:0.565442:0.815626:0.000000
S R S R:@0.586545:0.821493:0.651393:0.821493:0.651393:0.805087:0.586545:0.805087:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
2 1:@0.595645:0.824665:0.616700:0.824665:0.616700:0.815504:0.595645:0.815504:0.000000:0.000000:0.000000
–:@0.617296:0.822075:0.626500:0.822075:0.626500:0.804421:0.617296:0.804421:0.000000
1 2:@0.636612:0.824665:0.657668:0.824665:0.657668:0.815504:0.636612:0.815504:0.000000:0.000000:0.000000
nS –S:@0.594192:0.842615:0.637904:0.842615:0.637904:0.826209:0.594192:0.826209:0.000000:0.000000:0.000000:0.000000:0.000000
2:@0.613829:0.845788:0.619066:0.845788:0.619066:0.836627:0.613829:0.836627:0.000000
1:@0.638950:0.845788:0.644187:0.845788:0.644187:0.836627:0.638950:0.836627:0.000000
2:@0.644788:0.836554:0.650025:0.836554:0.650025:0.827394:0.644788:0.827394:0.000000
.:@0.663499:0.832698:0.666702:0.832698:0.666702:0.816985:0.663499:0.816985:0.000000
4. :@0.293660:0.867209:0.309730:0.867209:0.309730:0.851496:0.293660:0.851496:0.000000:0.000000:0.000000
Calcula el coeficiente óptimo de regresión lineal  ::@0.353907:0.867209:0.718096:0.867209:0.718096:0.851496:0.353907:0.851496:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
b:@0.705444:0.867129:0.714703:0.867129:0.714703:0.850723:0.705444:0.850723:0.000000
b:@0.554382:0.912585:0.563641:0.912585:0.563641:0.896179:0.554382:0.896179:0.000000
=:@0.564933:0.913243:0.580266:0.913243:0.580266:0.895589:0.564933:0.895589:0.000000
nR S R:@0.588235:0.901456:0.648686:0.901456:0.648686:0.885049:0.588235:0.885049:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
2:@0.608755:0.904628:0.613992:0.904628:0.613992:0.895467:0.608755:0.895467:0.000000
–:@0.614589:0.902038:0.623793:0.902038:0.623793:0.884384:0.614589:0.884384:0.000000
1 2:@0.633905:0.904628:0.654960:0.904628:0.654960:0.895467:0.633905:0.895467:0.000000:0.000000:0.000000
nS –S:@0.593683:0.922578:0.637396:0.922578:0.637396:0.906172:0.593683:0.906172:0.000000:0.000000:0.000000:0.000000:0.000000
2:@0.613320:0.925750:0.618557:0.925750:0.618557:0.916590:0.613320:0.916590:0.000000
1:@0.638441:0.925750:0.643678:0.925750:0.643678:0.916590:0.638441:0.916590:0.000000
2:@0.644279:0.916517:0.649516:0.916517:0.649516:0.907357:0.644279:0.907357:0.000000
.:@0.662990:0.912661:0.666193:0.912661:0.666193:0.896948:0.662990:0.896948:0.000000
Una recta en el plano :@0.080953:0.185241:0.207812:0.185241:0.207812:0.172385:0.080953:0.172385:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
no paralela al eje y es un :@0.080953:0.198857:0.225292:0.198857:0.225292:0.186001:0.080953:0.186001:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
conjunto definido como:@0.080953:0.212473:0.222878:0.212473:0.222878:0.199618:0.080953:0.199618:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
R:@0.080953:0.229664:0.088272:0.229664:0.088272:0.216240:0.080953:0.216240:0.000000
={(:@0.089115:0.230140:0.113348:0.230140:0.113348:0.215696:0.089115:0.215696:0.000000:0.000000:0.000000
x, y:@0.114176:0.229664:0.134357:0.229664:0.134357:0.216240:0.114176:0.216240:0.000000:0.000000:0.000000:0.000000
) ∊ℝ:@0.135231:0.230140:0.169087:0.230140:0.169087:0.215696:0.135231:0.215696:0.000000:0.000000:0.000000:0.000000
2:@0.170742:0.224701:0.175026:0.224701:0.175026:0.217206:0.170742:0.217206:0.000000
 | y a bx:@0.175516:0.229662:0.243062:0.229662:0.243062:0.216239:0.175516:0.216239:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
= +:@0.193513:0.230139:0.227851:0.230139:0.227851:0.215695:0.193513:0.215695:0.000000:0.000000:0.000000
}:@0.243920:0.230139:0.248936:0.230139:0.248936:0.215695:0.243920:0.215695:0.000000
,:@0.249764:0.229662:0.252384:0.229662:0.252384:0.216807:0.249764:0.216807:0.000000
donde :@0.080951:0.246853:0.122970:0.246853:0.122970:0.233997:0.080951:0.233997:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
b:@0.122729:0.246853:0.130304:0.246853:0.130304:0.233429:0.122729:0.233429:0.000000
∊ℝ:@0.131147:0.247329:0.155395:0.247329:0.155395:0.232885:0.131147:0.232885:0.000000:0.000000
 es la pendiente :@0.156223:0.246853:0.251475:0.246853:0.251475:0.233997:0.156223:0.233997:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de la recta, y :@0.080951:0.260469:0.155910:0.260469:0.155910:0.247613:0.080951:0.247613:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a:@0.155621:0.260469:0.163196:0.260469:0.163196:0.247046:0.155621:0.247046:0.000000
∊ℝ:@0.162985:0.260945:0.187233:0.260945:0.187233:0.246501:0.162985:0.246501:0.000000:0.000000
. Cuando :@0.188061:0.260469:0.243348:0.260469:0.243348:0.247613:0.188061:0.247613:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
b:@0.080936:0.274085:0.088511:0.274085:0.088511:0.260662:0.080936:0.260662:0.000000
>:@0.089355:0.274561:0.101900:0.274561:0.101900:0.260117:0.089355:0.260117:0.000000
0, la recta R tiene una :@0.102728:0.274085:0.229866:0.274085:0.229866:0.261229:0.102728:0.261229:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
inclinación a la derecha; :@0.080936:0.287701:0.222394:0.287701:0.222394:0.274845:0.080936:0.274845:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
cuando :@0.080936:0.301317:0.128979:0.301317:0.128979:0.288461:0.080936:0.288461:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
b:@0.080936:0.314933:0.088511:0.314933:0.088511:0.301510:0.080936:0.301510:0.000000
<:@0.089355:0.315409:0.101900:0.315409:0.101900:0.300965:0.089355:0.300965:0.000000
0, la recta R tiene una :@0.102728:0.314933:0.229866:0.314933:0.229866:0.302077:0.102728:0.302077:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
inclinación a la izquierda. :@0.080936:0.328549:0.228277:0.328549:0.228277:0.315693:0.080936:0.315693:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Asociada a este conjunto :@0.080936:0.342165:0.229610:0.342165:0.229610:0.329309:0.080936:0.329309:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
existe una función polinomial :@0.080936:0.355781:0.255752:0.355781:0.255752:0.342925:0.080936:0.342925:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
p de grado  1 de la forma::@0.080936:0.369397:0.238231:0.369397:0.238231:0.356541:0.080936:0.356541:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
≤:@0.147819:0.369874:0.160365:0.369874:0.160365:0.355429:0.147819:0.355429:0.000000
y p x:@0.080936:0.386587:0.121629:0.386587:0.121629:0.373164:0.080936:0.373164:0.000000:0.000000:0.000000:0.000000:0.000000
= ( )= +:@0.087894:0.387064:0.162654:0.387064:0.162654:0.372619:0.087894:0.372619:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a bx:@0.141690:0.386587:0.177865:0.386587:0.177865:0.373164:0.141690:0.373164:0.000000:0.000000:0.000000:0.000000
,    :@0.178724:0.386587:0.197911:0.386587:0.197911:0.373731:0.178724:0.373731:0.000000:0.000000:0.000000:0.000000:0.000000
∀ ∊ℝ:@0.198724:0.387064:0.244929:0.387064:0.244929:0.372619:0.198724:0.372619:0.000000:0.000000:0.000000:0.000000
x:@0.209598:0.386587:0.215697:0.386587:0.215697:0.373164:0.209598:0.373164:0.000000
 :@0.216540:0.386587:0.219839:0.386587:0.219839:0.373731:0.216540:0.373731:0.000000
,:@0.245758:0.386587:0.248378:0.386587:0.248378:0.373731:0.245758:0.373731:0.000000
de modo que su grafo :@0.080921:0.403778:0.213607:0.403778:0.213607:0.390922:0.080921:0.390922:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
G p:@0.080921:0.417394:0.101990:0.417394:0.101990:0.403970:0.080921:0.403970:0.000000:0.000000:0.000000
( )=:@0.089626:0.417870:0.119114:0.417870:0.119114:0.403426:0.089626:0.403426:0.000000:0.000000:0.000000:0.000000
R:@0.118888:0.417394:0.126208:0.417394:0.126208:0.403970:0.118888:0.403970:0.000000
.:@0.125997:0.417394:0.128617:0.417394:0.128617:0.404538:0.125997:0.404538:0.000000
Supongamos que se dispone :@0.080906:0.434584:0.254461:0.434584:0.254461:0.421728:0.080906:0.421728:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de la siguiente información::@0.080906:0.448200:0.241206:0.448200:0.241206:0.435344:0.080906:0.435344:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
S:@0.080906:0.465390:0.087502:0.465390:0.087502:0.451967:0.080906:0.451967:0.000000
={(:@0.087442:0.465867:0.109867:0.465867:0.109867:0.451422:0.087442:0.451422:0.000000:0.000000:0.000000
x y:@0.109792:0.465390:0.132822:0.465389:0.132822:0.451966:0.109792:0.451967:0.000000:0.000000:0.000000
i:@0.115889:0.467984:0.117724:0.467984:0.117724:0.460490:0.115889:0.460490:0.000000
 , :@0.117686:0.465389:0.126782:0.465389:0.126782:0.452533:0.117686:0.452533:0.000000:0.000000:0.000000
i:@0.132765:0.467984:0.134600:0.467984:0.134600:0.460490:0.132765:0.460490:0.000000
) ∊ ℝ:@0.134561:0.465865:0.170375:0.465865:0.170375:0.451421:0.134561:0.451421:0.000000:0.000000:0.000000:0.000000:0.000000
2:@0.170149:0.460428:0.174434:0.460428:0.174434:0.452933:0.170149:0.452933:0.000000
 | :@0.174396:0.465389:0.184065:0.465389:0.184065:0.452533:0.174396:0.452533:0.000000:0.000000:0.000000
i:@0.183990:0.465389:0.187092:0.465389:0.187092:0.451966:0.183990:0.451966:0.000000
=:@0.187032:0.465865:0.199577:0.465865:0.199577:0.451421:0.187032:0.451421:0.000000
1, …,  . :@0.199502:0.465389:0.251928:0.465389:0.251928:0.452533:0.199502:0.452533:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
n:@0.233358:0.465389:0.241129:0.465389:0.241129:0.451966:0.233358:0.451966:0.000000
}:@0.241069:0.465865:0.246084:0.465865:0.246084:0.451421:0.241069:0.451421:0.000000
En la Figura 4.7 se ilustra un :@0.080946:0.482579:0.242358:0.482579:0.242358:0.469723:0.080946:0.469723:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
conjunto de puntos que :@0.080946:0.496195:0.225908:0.496195:0.225908:0.483339:0.080946:0.483339:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
siguen una tendencia o :@0.080946:0.509811:0.221168:0.509811:0.221168:0.496955:0.080946:0.496955:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
apariencia de una recta, así :@0.080946:0.523427:0.240072:0.523427:0.240072:0.510571:0.080946:0.510571:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
como la gráfica de la recta de :@0.080946:0.537043:0.253989:0.537043:0.253989:0.524188:0.080946:0.524188:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
ecuación cartesiana:  :@0.080946:0.550659:0.204487:0.550659:0.204487:0.537804:0.080946:0.537804:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
y a bx:@0.080946:0.564275:0.137453:0.564275:0.137453:0.550852:0.080946:0.550852:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
= +:@0.087904:0.564752:0.122242:0.564752:0.122242:0.550308:0.087904:0.550308:0.000000:0.000000:0.000000
,    :@0.138311:0.564275:0.157498:0.564275:0.157498:0.551420:0.138311:0.551420:0.000000:0.000000:0.000000:0.000000:0.000000
∀ ∊ℝ:@0.158312:0.564752:0.200376:0.564752:0.200376:0.550308:0.158312:0.550308:0.000000:0.000000:0.000000:0.000000
x:@0.169185:0.564275:0.175285:0.564275:0.175285:0.550852:0.169185:0.550852:0.000000
.:@0.201204:0.564275:0.203824:0.564275:0.203824:0.551420:0.201204:0.551420:0.000000
Figura 4.7:@0.140164:0.588614:0.199314:0.588614:0.199314:0.574975:0.140164:0.574975:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
0:@0.090900:0.701042:0.097433:0.701042:0.097433:0.689615:0.090900:0.689615:0.000000
x:@0.250962:0.702341:0.256705:0.702341:0.256705:0.690913:0.250962:0.690913:0.000000
y:@0.090745:0.602148:0.096087:0.602148:0.096087:0.590650:0.090745:0.590650:0.000000
y a bx:@0.200133:0.608236:0.245647:0.608236:0.245647:0.596738:0.200133:0.596738:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
= +:@0.205473:0.608519:0.234014:0.608519:0.234014:0.595679:0.205473:0.595679:0.000000:0.000000:0.000000
Competencia :@0.080953:0.145303:0.189513:0.145303:0.189513:0.128356:0.080953:0.128356:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
matemática :@0.080953:0.161945:0.178428:0.161945:0.178428:0.144998:0.080953:0.144998:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
MUESTRA EDITORIAL:@0.248902:0.947499:0.888171:0.113285:0.743922:0.050540:0.104653:0.884754:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 Muestra editorial solo para fines didácticos – Prohibida su venta:@0.095585:0.659700:0.095585:0.341447:0.077558:0.341447:0.077558:0.659700:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000