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EastWind [94]
1 year ago
10

What are the solutions of this quadratic equation?X2 - 10x= -34A.r=-8, -2B.r= 5 + 3iC.r=-5 + 3iD.r=-5 + 159

Mathematics
1 answer:
ololo11 [35]1 year ago
5 0

The given equation is-

x^2-10x=-34

First, we move the independent term to the other side.

x^2-10x+34=0

Now, we have to use the quadratic equation to find the solutions.-

x_{1,2}=\frac{-b\pm\sqrt[]{b^2-4ac}}{2a}

Where, a = 1, b = -10, and c = 34.

Replacing these values in the formula, we have.

\begin{gathered} x_{1,2}=\frac{-(-10)\pm\sqrt[]{(-10)^2-4(1)(34)}}{2(1)} \\ x_{1,2}=\frac{10\pm\sqrt[]{100-136}}{2}=\frac{10\pm\sqrt[]{-36}}{2} \end{gathered}

But, there's no square root of -36 because it's a negative. To solve this issue, we use complex numbers that way, we would have solutions.

x_{1,2}=\frac{10\pm\sqrt[]{36}i}{2}=\frac{10\pm6i}{2}=5\pm3i<h2>Therefore, the solutions are</h2>\begin{gathered} x_1=5+3i \\ x_2=5-3i \end{gathered}The right answer is B.
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An accounting firm is planning for the next tax preparation season. From last years returns, the firm collects a systematic rand
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And the standard error for the mean would be:

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And we can use the z score formula given by:

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And replacing we got:

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And we can find this probability with the complement rule and the normal standard deviation or excel and we got:

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Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Solution to the problem

Part a

From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

And the standard error for the mean would be:

\sigma_{\bar X}= \frac{140}{\sqrt{100}} =14

Part b

We want this probability:

P(\bar X >120)

And we can use the z score formula given by:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

z = \frac{120-90}{\frac{140}{\sqrt{100}}}= 2.143

And we can find this probability with the complement rule and the normal standard deviation or excel and we got:

P( z>2.143) = 1-P(Z

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Step-by-step explanation:

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The sum of the coefficients is 1 - 2 - 19 + 20 = 0

This means that x = 1 is a root and (x - 1) is a factor of f(x)

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