3 fraction equivalent to 4/7

Mathematics

2 answers:

ddd [48]3 years ago

7 0

1. 28/49 2. 32/56 3. 36/63

GalinKa [24]3 years ago

4 0

Answer: 8/14, 12/21, and 288/504

Step-by-step explanation: To find 3 fractions that are equivalent to 4/7, we either multiply or divide the numerator and denominator by the same number.

If we multiply 4/7 by 2 in both the numerator and denominator, we get the equivalent fraction 8/14.

If we multiply 4/7 by 3 in both the numerator and denominator, we get the equivalent fraction 12/21.

If we multiply 4/7 by 72 in both the numerator and denominator, we get the equivalent fraction 288/504.

These are just 3 possible answers.

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A candidate for one of Ohio's two U.S. Senate seats wishes to compare her support among registered voters in the northern half o

Radda [10]

Answer:

$(0.531-0.45) - 1.96 \sqrt{\frac{0.531(1-0.531)}{2000} +\frac{0.45(1-0.45)}{2000}}=0.050$

$(0.531-0.45) + 1.96 \sqrt{\frac{0.531(1-0.531)}{2000} +\frac{0.45(1-0.45)}{2000}}=0.112$

And the best option for this case would be:

A. 0.050 to 0.112.

Step-by-step explanation:

Data given

$p_A$ represent the real population proportion of who support the cnadite for the northern half state

$\hat p_A =\frac{1062}{2000}=0.531$ represent the estimated proportion of who support the candidate for the northern half state

$n_A=2000$ is the sample size required the northern half state

$p_B$ represent the real population proportion of who support the candidate for the southern half state

$\hat p_B =\frac{900}{2000}=0.45$ represent the estimated proportion of people who support the candidate for the southern half state

$n_B=2000$ is the sample size for the northern half state

$z$ represent the critical value

The confidence interval for the difference of two proportions would be given by this formula

$(\hat p_A -\hat p_B) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_B (1-\hat p_B)}{n_B}}$

For the 95% confidence interval the value of $\alpha=1-0.95=0.05$ and $\alpha/2=0.025$ , with that value we can find the quantile in the normal standard distribution and we got.