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Nana76 [90]
3 years ago
9

Write two equivalent ratios for 4:7

Mathematics
2 answers:
Verdich [7]3 years ago
5 0

the answers for the number 4 are

8,12

and the answers for 7 are

14,21

saul85 [17]3 years ago
5 0
8:14 and 12:21 because you just have to multiply each number in the ratio by the same number and if your not sure you have the right answers then just divide both numbers
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7.406

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7.406 in standard form

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For a tile pattern with the rule y = 6x + 4 (where x represents the figure number and y
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Step-by-step explanation:

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Help Find the value of x and the value of y.
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Answer:

x = 2sqrt(2)

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A sample of 200 observations from the first population indicated that X1 is 170. A sam- ple of 150 observations from the second
nikitadnepr [17]

Answer:

a. If the P-value is smaller than the significance level, the null hypothesis is rejected.

b. Pooled proportion = 0.8

c. z = 2.7

d. As the P-value (0.0072) is smaller than the significance level (0.05), the null hypothesis is rejected.

There is enough evidence to support the claim that the proportions differ significantly.

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

We will use the P-value approach, so the decision rule is that if the P-value is lower than the significance level, the null hypothesis is rejected.

The claim is that the proportions differ significantly.

Then, the null and alternative hypothesis are:

H_0: \pi_1-\pi_2=0\\\\H_a:\pi_1-\pi_2\neq 0

The significance level is 0.05.

The sample 1, of size n1=200 has a proportion of p1=0.85.

p_1=X_1/n_1=170/200=0.85

The sample 2, of size n2=150 has a proportion of p2=0.7333.

p_2=X_2/n_2=110/150=0.7333

The difference between proportions is (p1-p2)=0.1167.

p_d=p_1-p_2=0.85-0.7333=0.1167

The pooled proportion, needed to calculate the standard error, is:

p=\dfrac{X_1+X_2}{n_1+n_2}=\dfrac{170+110}{200+150}=\dfrac{280}{350}=0.8

The estimated standard error of the difference between means is computed using the formula:

s_{p1-p2}=\sqrt{\dfrac{p(1-p)}{n_1}+\dfrac{p(1-p)}{n_2}}=\sqrt{\dfrac{0.8*0.2}{200}+\dfrac{0.8*0.2}{150}}\\\\\\s_{p1-p2}=\sqrt{0.0008+0.00107}=\sqrt{0.00187}=0.0432

Then, we can calculate the z-statistic as:

z=\dfrac{p_d-(\pi_1-\pi_2)}{s_{p1-p2}}=\dfrac{0.1167-0}{0.0432}=\dfrac{0.1167}{0.0432}=2.7

This test is a two-tailed test, so the P-value for this test is calculated as (using a z-table):

P-value=2\cdot P(z>2.7)=0.0072

As the P-value (0.0072) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is enough evidence to support the claim that the proportions differ significantly.

6 0
3 years ago
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