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Sindrei [870]
3 years ago
9

The quantity y varies directly with the square of x and inversely with z. When x is 9 and z is 27, y is 6. What is the constant

of variation?


2

18

54
Mathematics
1 answer:
ira [324]3 years ago
4 0
\bf \qquad \qquad \textit{double proportional variation}
\\\\
\begin{array}{llll}
\textit{\underline{y} varies directly with \underline{x}}\\
\textit{and inversely with \underline{z}}
\end{array}\implies y=\cfrac{kx}{z}\impliedby 
\begin{array}{llll}
k=constant\ of\\
\qquad  variation
\end{array}\\\\
-------------------------------

\bf \stackrel{\textit{\underline{y} varies directly with the square of \underline{x} and inversely with \underline{z}}}{y=\cfrac{kx^2}{z}}
\\\\\\
\textit{we also know that }
\begin{cases}
x=9\\
z=27\\
y=6
\end{cases}\implies 6=\cfrac{k9^2}{27}
\\\\\\
\cfrac{27\cdot 6}{9^2}=k\implies 2=k
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We conclude that we fail to reject H_0 as there is not sufficient evidence to warrant support of the claim that less than 10 percent of the test results are wrong.

Step-by-step explanation:

We are given that among 317 tested​ subjects, results from 25 subjects were wrong.

We have to test the claim that less than 10 percent of the test results are wrong.

<u><em>Let p = proportion of subjects that were wrong.</em></u>

So, Null Hypothesis, H_0 : p = 10%     {means that 10 percent of the test results are wrong}

Alternate Hypothesis, H_A : p < 10%     {means that less than 10 percent of the test results are wrong}

The test statistics that would be used here <u>One-sample z proportion</u> <u>statistics</u>;

                      T.S. =  \frac{\hat p-p}{\sqrt{\frac{\hat p (1-\hat p)}{n} } }  ~ N(0,1)

where, \hat p = sample proportion of test results that were wrong = \frac{25}{317} = 0.08

           n = sample of tested subjects = 317

So, <u><em>test statistics</em></u>  =  \frac{0.08-0.10}{\sqrt{\frac{0.08 (1-0.08)}{317} } }

                              =  -1.31

The value of z test statistics is -1.31.

Now, the P-value of the test statistics is given by the following formula;

                P-value = P(Z < -1.31) = 1 - P(Z \leq 1.31)

                              = 1 - 0.9049 = <u>0.095</u>

<u><em>Now, at 0.05 significance level the z table gives critical value of -1.645 for left-tailed test.</em></u><em> Since our test statistics is more than the critical value of z as -1.31 > -1.645, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which </em><em><u>we fail to reject our null hypothesis</u></em><em>.</em>

Therefore, we conclude that we fail to reject H_0 as there is not sufficient evidence to warrant support of the claim that less than 10 percent of the test results are wrong.

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