4/3 * pi * r^3
4/3 * 3.14 * 10^3
4/3 * 3.14 * 1000
4/3 * 3140 = 4186.66 rounds to 4187 in^3
Answer:
d. Both I and II are false
Step-by-step explanation:
When there is a high degree of linear correlation between the predictors the errors are found.
The basic objective of the regression model is to separate the dependent and independent variables. So if the variables have high degree of linear correlation then the multi collinearity causes problems or has errors. It is not necessary that multi collinearity must be present with high degree of linear correlation.
For example we have 3 variable of heat length and time. And all of them have a high degree of correlation. With increase in heat and time the length increases . But for multi collinearity with the increase of time and decrease of heat length does not increase. So this causes errors.
y-hat = 135 + 6x + errors
The linear relationship between height and weight is inexact. The deterministic relation in such cases is then modified to allow the inexact relationship between variables and a non deterministic or probabilistic model is obtained which has error which are unknown random errors.
y- hat= a + bXi + ei (i=1,2,3...)
ei are the unknown random errors.
<u><em>So both statements are false.</em></u>
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Answer:
Area of wall = 360 ft²
Step-by-step explanation:
Given:
One part of wall (Rectangle) = 16ft x 18ft
Another part of wall (Triangle) = 8ft x 18ft
Find:
Area of wall
Computation:
Area of wall = Area of rectangle + Area of triangle
Area of wall = (l x b) + (1/2)(b)(h)
Area of wall = (16 x 18) + (1/2)(8)(18)
Area of wall = 288 ft² + 72 ft²
Area of wall = 360 ft²
Subtract 7 from both sides leaving you with
26=-2a
Divide -2 from both sides leaving to you then with
-13=a and this is the answer
