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Ksivusya [100]
4 years ago
10

Math question down below

Mathematics
1 answer:
Gemiola [76]4 years ago
4 0
Oh all you do is however many numbers in the chart are the same. on the line put how many of each of them. like since there are three 7.5 in the 7.5 place you put how many there were.
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Answer:

A survey among 500 grade 3 pupils revealed that 150 of them stayin the playground after their classes. Use 95% confidence to conduct a test of proportion. 1 1.

Step-by-step explanation:

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What equation has a slope of 2 and contains (1,4)
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Step-by-step explanation:

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What are the 3 main properties of distribution across earth?
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To plan the budget for next year a college must update its estimate of the proportion of next year's freshmen class that will ne
Naily [24]

Answer:

Null hypothesis:p\leq 0.35  

Alternative hypothesis:p > 0.35  

z=\frac{0.447 -0.35}{\sqrt{\frac{0.35(1-0.35)}{150}}}=2.491  

p_v =P(z>2.491)=0.0064  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of applicants who request financial aid is significantly higher than 0.35

Step-by-step explanation:

Data given and notation

n=150 represent the random sample taken

X=67 represent the applicants who request financial aid

\hat p=\frac{67}{150}=0.447 estimated proportion of applicants who request financial aid

p_o=0.35 is the value that we want to test

\alpha represent the significance level

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion of applicants who request financial aid is higher than 0.35.:  

Null hypothesis:p\leq 0.35  

Alternative hypothesis:p > 0.35  

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

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

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

Calculate the statistic  

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

z=\frac{0.447 -0.35}{\sqrt{\frac{0.35(1-0.35)}{150}}}=2.491  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The next step would be calculate the p value for this test.  

Since is a right tailed test the p value would be:  

p_v =P(z>2.491)=0.0064  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of applicants who request financial aid is significantly higher than 0.35

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The numbers on two consecutively numbered gym lockers have a sum of 151. What are the locker​ numbers?
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75 and 76. Hope this helps ;)
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