The distance is 3, because 7 - 4 = 3.
Answer:
Step-by-step explanation:
So, according to the law of Sines, we have
In our case, we have S and R, so...
And we want to isolate R...
the angle of R is then 75.90 degrees.
Answer is D. last one
2 * 3 = 6
On the number line, 0 to 3, it's 3 units
then 3 to 6, there's another 3 units
so 2 x 3(units) = 6
Answer:
a. Scale Perimeter : 2.5 centimeters
Actual Perimeter : 13 centimeters
Actual Area : 10.5 square centimeters
b. Actual Perimeter : 130 mm
Actual Area : 1,050 mm
Step-by-step explanation:
a. 2.5 mm = 0.25 cm
2 (1 + 0.25) = 2.5
2 (3.5 + 3) = 13
3.5 x 3 = 10.5
b. 3.5 cm = 35 mm 3 cm = 30 mm
2 (35 + 30) = 130
35 x 30 = 1050
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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