Question

use the least - squares regression line of this data set to predict a value. maura has noticed that her bike ride to work takes longer on some days than others. she is curious to see how the morning temperature is related to the duration of her commute. for the past several mornings, she measured the temperature (in celsius), x, and the time her commute had taken (in minutes), y. the least squares regression line of this data set is: y = - 2.222x + 51.758. how long does this line predict mauras commute will take when the temperature is 2.68 degrees celsius? round your answer to the nearest thousandth.

Explanation:

Step1: Identificar la ecuación de la recta

La ecuación de la recta de regresión es $y = - 2.222x+51.758$.

Step2: Sustituir el valor de x

Sustituimos $x = 2.68$ en la ecuación. Entonces $y=-2.222\times2.68 + 51.758$.

Step3: Realizar los cálculos

Primero, calculamos $-2.222\times2.68=-5.95496$. Luego, $y=-5.95496 + 51.758$. Finalmente, $y = 45.80304$.

Step4: Redondear el resultado

Redondeamos a la milésima más cercana. $y\approx45.803$.

Answer:

$45.803$