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sattari [20]
3 years ago
15

You collect a total of $75 in donations from three people. The three donations are in the ratio 4 to 4 to 7. How much is each of

the smaller donations? And how much greater is the largest donation then one of the smaller donations?
Mathematics
1 answer:
worty [1.4K]3 years ago
7 0
Each smaller donation was for $20 The largest donation was $15 greater than the smaller donation. First, determine the size of each donation. Since they are in a ratio of 4:4:7, it's easiest to add the ratios together (4+4+7) = 15. Then divide the total donation by that sum (75/15) = 5. Finally, multiply 5 by each of the ratios. 5 * 4 = 20, 5 * 4 = 20, and 5 * 7 = 35 So the 2 smaller donations were $20 each, and the largest donation was for $35. The largest donation was $35 - $20 = $15 larger than one of the smaller donations.
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Elodia [21]

Answer:

The answer to your question is below

Step-by-step explanation:

1) Alternate interior angles measure the same

       10x - 10° = 100°

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            (12x + 8) + (100°) = 180°

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8) Consecutive interior angles measure 180°

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9) Corresponding angles measure the same

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Answer:

We conclude that there is difference in the proportion of deaths between the 2 groups.

Step-by-step explanation:

We are given that among 2823 drivers not wearing seat belts, 31 died as a result of injuries, and among 7765 drivers wearing seat belts 16 were killed.

Let p_1 = <u><em>proportion of deaths when drivers were not wearing seat belts.</em></u>

p_2 = <u><em>proportion of deaths when drivers were wearing seat belts.</em></u>

So, Null Hypothesis, H_0 : p_1=p_2      {means that there is no difference in the proportion of deaths between the 2 groups}

Alternate Hypothesis, H_A : p_1\neq p_2     {means that there is difference in the proportion of deaths between the 2 groups}

The test statistics that would be used here <u>Two-sample z test for proportions;</u>

                          T.S. =  \frac{(\hat p_1-\hat p_2)-(p_1-p_2)}{\sqrt{\frac{\hat p_1(1-\hat p_1)}{n_1}+\frac{\hat p_2(1-\hat p_2)}{n_2} } }  ~ N(0,1)

where, \hat p_1 = sample proportion of deaths when drivers were not wearing seat belts = \frac{31}{2823} = 0.011

\hat p_2 = sample proportion of deaths when drivers were wearing seat belts = \frac{16}{7765} = 0.002

n_1 = sample of drivers not wearing seat belts = 2823

n_2 = sample of drivers wearing seat belts = 7765

So, <u><em>the test statistics</em></u>  =  \frac{(0.011-0.002)-(0)}{\sqrt{\frac{0.011(1-0.011)}{2823}+\frac{0.002(1-0.002)}{7765} } }

                                       =  4.438

The value of z test statistics is 4.438.

<u>Now, at 5% significance level the z table gives critical values of -1.96 and 1.96 for two-tailed test.</u>

Since our test statistic doesn't lie within the range of critical values of z, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u>we reject our null hypothesis</u>.

Therefore, we conclude that there is difference in the proportion of deaths between the 2 groups.

Also, <u>Margin of error</u> (E) =  1.96 \times \sqrt{\frac{\hat p_1(1-\hat p_1)}{n_1}+\frac{\hat p_2(1-\hat p_2)}{n_2} }

                                        =  1.96 \times \sqrt{\frac{0.011(1-0.011)}{2823}+\frac{0.002(1-0.002)}{7765} }

                                        =  <u>0.00397</u>

5 0
3 years ago
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