which is valid for
The quadratic regression equation that models these data is y = - 0.34x ^ 2 + 4.43x + 3.46 Using the quadratic regression equati
on what was the predicted profit in year 8? A. $ 17.14 million B. $ 17 million C. $ 16.8 million D. $16 million
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which is valid for
The expression is called as <u>option d)</u> Quartic Trinomial.
<u>Step-by-step explanation:</u>
The given expression is .
<u>To find the number of terms :</u>
- one-term polynomial is called a monomial
- two-term polynomial is called a binomial and
- three-term polynomial is called a trinomial
"The number of terms in the expression is Three."
<u>The three terms are as follows :</u>
⇒ First term is
⇒ Second term is 15x³
⇒ Third term is 53x²
Therefore, the given expression is called a "trinomial" with respect to the number of terms in it.
<u>To find the degree :</u>
The degree of a polynomial is the highest of the degrees of the individual terms in it with non-zero coefficients.
Here, in this expression the highest degree is 4.
Fourth degree is known as "Quartic".
Now, combining the number of terms and degree in the given expression, it is known as "Quartic Trinomial" which is option D).
a) The estimate of the proportion of defectives when the process is in control is 0.054
b) The standard error of the proportion if the sample size is 100 is 0.0226.
c) The upper control limit is 0.1218 and the lower control limit is 0 (since LCL < 0 and p > 0, we can write LCL = 0).
<h3>What are the formulas for finding the estimate of the proportion, standard variation, and control limits?</h3>1) The estimate of the proportion of success is
p = (number of success)/(total number of samples)
I.e., p = x/N
2) The standard deviation of the proportion of success is
3) The upper and lower control limits for a control chart are:
L.C.L = p - 3
and U.C.L = p + 3
It is given that, there are 25 samples of 100 items each.
So, the total number of items i.e., the total sample size,
N = 25 × 100 = 2500
In 25 samples, a total of 135 items were found to be defective.
So, the number of defectives x = 135
a) The estimate of the proportion of defectives is p = x/N
On substituting, we get
p = 135/2500 = 0.054
b) The standard error of the proportion if the sample of size 100 is calculated by
On substituting p = 0.054 and n = 100, we get
= 0.0226
c) The control limits for the control chart are:
Upper control limit = p + 3
⇒ U.C.L = 0.054 + 3(0.0226) = 0.054 + 0.0678 = 0.1218
Lower control limit = p - 3
⇒ L.C.L = 0.054 - 3(0.0226) = 0.054 - 0.0678 = - 0.0138 ≈ 0
(Since we know that the lower control limit should not be a negative value, it is made equal to 0).
Learn more about an estimate of the proportion here:
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