It's not the difference of squares, rather it is the square of a difference. That leaves a perfect square trinomial, which narrows your selection to two choices. An expression with 2 terms is not a trinomial, so that further narrows your selection. The appropriate choice is
... (4xy -3z)² = 16x²y² -24xyz +9z², a perfect square trinomial
_____
The expression you have in your problem statement has no z term, so none of the choices is applicable to that one.
Answer:
PB = 1.8
Step-by-step explanation:
PQ = 8 cm, BC = 10 cm and AB = 9 cm
∆ABC is similar to ∆APQ.
Therefore:
Plug in the values
Cross multiply
AP × 10 = 8 × 9
AP × 10 = 72
Divide both sides by 10
AP = 7.2
PB = AB - AP
PB = 9 - 7.2
PB = 1.8
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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Your decimal is in the wrong place.
However, assuming the number is 50,000, the answer could be 49987.
Assuming the number is 500,000, the answer could be 499954.
