Answer:
The answer is B. There are infinitely many solutions.
Step-by-step explanation:
None of the other answers make sense and do not work.
Hope This Helps!
A x2−9
B x3−9
C (x+9)2
D (x−9)2
I know the answer is either A or B i might be wrong tho pls help im not sure.
Answer:
A
Step-by-step explanation:
In this question, we are concerned with selecting which of the options best represents the difference of two squares.
Let’s have an exposition below as follows;
Consider two numbers, which are perfect squares and can be expressed as a square of their square roots;
a^2 and b^2
where a and b represents the square roots of the numbers respectively.
Inserting a difference between the two, we have;
a^2 - b^2
Now by applying the difference of two squares, these numbers will become;
a^2 - b^2 = (a + b)(a-b)
So our answer out of the options will be that option that could be expressed as above.
The correct answer to this is option A
Kindly note that;
x^2 -9 can be expressed as x^2 - 3^2 and consequently, this can be written as;
(x-3)(x + 3)
January February March April May June
Acutal 120 140 150 140 150 130
Predicted 80 150 110 150 110 150
Residual 40 −10 40 −10 40 −20
Analyze the data. Determine whether the equation that produced the predicted values represents a good line of best fit.
No, the equation is not a good fit because the residuals are all far from zero.
No, the equation is not a good fit because the sum of the residuals is a large number.
Yes, the equation is a good fit because the residuals are not all far from zero.
Yes, the equation is a good fit because the sum of the residuals is a small number.
The equation that produced these predicted values is not a good fit given that the sum of the residuals is a large number.
The sum of the residuals in a regression is a value that is always supposed to be almost equal to zero in a regression analysis.
The residual tells us that the error term has been reduced to the minimum in the regression analysis.
Read more on a regression analysis here:
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