Answer:
In this scenario, we will use the <u>femur or the thigh</u> bone length as the explanatory variable.
Step-by-step explanation:
Dependent variables are those variables that are under study, i.e. they are being observed for any changes when the other variables in the model are changed.
The dependent variables are also known as response variables.
Independent variables are the variables that are being altered to see a proportionate change in the dependent variable. In a regression model there can be one or more than one independent variables.
The independent variables are also known as the explanatory variables.
Scientifically it is believed that the length of arm and legs are related and basically grow at the same time.
So, in this case the explanatory variable can either of the two bone lengths.
Thus, the complete statement is:
"In this scenario, we will use the <u>femur or the thigh</u> bone length as the explanatory variable."
a) For x = 27:
z = 27-28/2 = -0.5
For x = 31:
z = 31-38/2 = 1.5
From the normal distribution table, P(27 < x < 31) = P(-0.5 < z < 1.5) = P(z < 1.5) - P(z < -0.5) = 0.9332 - 0.3085 = 62.47%
b) For x > 30.2:
z = 30.2-28/2 = 1.1
From the normal distribution table, P(x > 30.2) = P(z > 1.1) = 1 - P(z > 1.1) = 1 - 0.8643 = 13.57%
The answer is 0.5! Good luck
