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podryga [215]
4 years ago
12

The ratio of a basketball player's completed free throws to attempted free throws is 4 to 7. if she completed 12 free throws, fi

nd how many free throws she attempted.
a. 3 free throwsc.21 free throwsb.7 free throwsd.4 free throws
Mathematics
2 answers:
Artemon [7]4 years ago
6 0
Ratio of the free throws completed to attempted free throws is given to be 4:7. This ratio should be equal to the ratio of the next case. Let x be the number of free throws attempted. The proportion takes a form of,                  
                    (4 completed / 7 attempted) = (12 completed / x attempted)
Solving for x gives x = 21. Thus, the answer is letter c. which is the second among the choices. 
svp [43]4 years ago
4 0

The correct answer is:

C. 21 free throws

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According to a Pew Research Center study, in May 2011, 35% of all American adults had a smart phone (one which the user can use
taurus [48]

Answer:

z=\frac{0.4 -0.35}{\sqrt{\frac{0.35(1-0.35)}{300}}}=1.82  

p_v =P(z>1.82)=0.034  

So the p value obtained was a very low value and using the significance level given \alpha=0.1 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis

And the best conclusion would be:

There is enough evidence to show that more than 35% of community college students own a smart phone (Pvalue = 0.034).

And for the second case the correct system of hypothesis is:

H0: p = 0.078; Ha: p > 0.078

Step-by-step explanation:

Data given and notation

n=300 represent the random sample taken

\hat p=\frac{120}{300}=0.4 estimated proportion of college students that have a smart phone

p_o=0.35 is the value that we want to test

\alpha=0.1 represent the significance level

Confidence=90% or 0.90

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 proportion is >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{0.4 -0.35}{\sqrt{\frac{0.35(1-0.35)}{300}}}=1.82  

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 significance level provided \alpha=0.1. 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>1.82)=0.034  

So the p value obtained was a very low value and using the significance level given \alpha=0.1 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis

And the best conclusion would be:

There is enough evidence to show that more than 35% of community college students own a smart phone (Pvalue = 0.034).

And for the second case the correct system of hypothesis is:

H0: p = 0.078; Ha: p > 0.078

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8/2 = 4 it is the ratio
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Answer:

x = -9

Step-by-step explanation:

4x+10=-26

Subtract 10 from each side

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Divide each side by 4

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Step-by-step explanation:

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