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abruzzese [7]
3 years ago
8

Emily and Sarah had a total of $80. after Sarah spent 1/3 of her money and Emily spent $17, Emily had twice as much money as Sar

ah. how much more money did Emily have then Sarah at first?
Mathematics
1 answer:
Phoenix [80]3 years ago
3 0
<span> SO in total, Emily and Sarah had a total of 80 dollars in which Emily had twice as much as Sarah.
Let’s solve to find out how much their Money is.
=> Since the ratio of the given data is 2:1, 2 + 1 =3, so let’s divide 80 by 3
=> 80 / 3 = 26.667 ,
=> Emily has twice as this.
=> 26.667 * 2 = 53.33
=> Sarah has 26.67
Now, Sarah spent 1/3 of her money
=> 26.67 / 3 = 8.89 – her remaining money
Emily spent 17 dollars of her money
=> 53.33 – 17 = 36.33</span>



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Step-by-step explanation:

1) Data given and notation

n=500 represent the random sample taken

X=380 represent the number of people with some characteristic

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p_o=0.76 is the value that we want to test

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2) Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion is 0.7 .:  

Null hypothesis:p=0.77  

Alternative hypothesis:p \neq 0.77  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

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The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

<em>Check for the assumptions that he sample must satisfy in order to apply the test </em>

a)The random sample needs to be representative: On this case the problem no mention about it but we can assume it.

b) The sample needs to be large enough

np_o =500*0.77=385>10

n(1-p_o)=384*(1-0.77)=115>10

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Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.76-0.77}{\sqrt{\frac{0.77(1-0.77)}{500}}}=-0.531  

4) Statistical decision  

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The significance level provided \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a bilateral test the p value would be:  

p_v =2*P(z  

If we compare the p value and using the significance level given \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion is not significantly different from 0.77.  

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