John's parents recorded his height at various ages between 36 and 66 months. Below is the equation of the least-squares regression line of John's height (inches) on age (months) based on John's records. John's parents decide to use the least-squares regression line of John's height on age to predict his height at age 16 years (192 months). What conclusion can we draw? John's height, in inches, should be about half his age, in months. Such a prediction could be misleading, because it involves extrapolation. The parents will get a fairly accurate estimate of his height at age 16 years, because the data are clearly correlated.

The parents will have fairly accurate estimate of his height at age 16 years

Step-by-step explanation:

Below is a record of the results which is missing in the question:

Age(A,months) 36 48 54 60 66

Height(H, inches) 34 38 41 43 45

The equation which is missing in the question is :

Height= 0.7471× months

The above model can be used to get a fairly accurate estimate of John's height at the age of 16 years becasue the data are corelated by the equation.

step-by-step explanation:

if you meant, "on the way from (3, 2) to (3, 14):

x does not change; y increases by 12.

ensure that you have copied down this problem correctly.   .

hello,

b) 62.47% of the students are between 14 and 18 years old.

step-by-step explanation:

mean = 15 and standard deviation = 2

student between 14 to 18

formula used z-score

for age 14 , z score

using z-table , p(z> -0.5)=0.3085

for age 18 , z score

using z-table , p(z< 1.5)=0.9332

p(-0.5< z< 1.5)=0.9332-0.3085 = 0.6247

thus, 62.47% of the students are between 14 and 18 years old.

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