Respuesta :
Answer:
1. -0.9148
2. the weight predicted of newborn was too high for that length.
Step-by-step explanation:
The regression equation relates the length (cm) of newborn boys to their weight in kg.
W=-5.33+0.1926l where W is the weight in kg and l is length in cm
To get the residual, you calculate the difference between the observed value and the predicted value
Residual=observed value- predicted value
Given the newborn was 48 cm long and 3kg in weight then predicted weight is;
W=-5.33+0.1926l
W=-5.33+0.1926*48
W=-5.33+9.2448
W=3.9148 kg
Residual= 3-3.9148 = -0.9148
A negative residual mean that the prediction for the weight was too high with the corresponding length of the newborn.
The least squares regression line minimizes the vertical distance between
the data points and the regression line
- The residual is -0.9148 kg
- The negative residual indicates that the baby's weight is lower than predicted
Reasons:
Known parameters;
The least squares regression line equation is [tex]\hat y = a + b \cdot x[/tex]
Given length of the newborn baby = 48 cm
Weight of the newborn baby = 3 kg
Given regression line equation; Weight = -5.33 + 0.1926 × Length
Required:
The residual (weight) of the newborn baby boy
Solution:
The given equation can be presented as; [tex]\hat y[/tex] = -5.33 + 0.1926·x
The predicted weight of the baby is [tex]\hat y[/tex] = -5.33 + 0.1926 × 48 = 3.9148
The residual, [tex]e_i[/tex] = [tex]y_i - y_{predicted}[/tex]
∴ The residual of the weight of the newborn is 3 kg - 3.9148 kg = -0.9148 kg
From the negative residual, what can be said is that the
A negative residual is an indication of a too high predicted value
The negative residual means that the baby's weight is lower than predicted
Learn more here:
https://brainly.com/question/16975425
