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iren2701 [21]
3 years ago
9

The quadrilaterals ABCD and PQRS are similar. Find the length X of SP.

Mathematics
1 answer:
BaLLatris [955]3 years ago
6 0

Answer:

x = 3.6

Step-by-step explanation:

Since Quadrilateral ABCD ~ PQRS, therefore:

\frac{AB}{PQ} = \frac{BC}{QR} = \frac{CD}{RS} = \frac{DA}{SP}

Let's find the value of x by using the ratio of two corresponding sides of both quadrilaterals. Let's use:

\frac{CD}{RS} = \frac{DA}{SP}

CD = 5

RS = 4.5

DA = 4

SP = x

\frac{5}{4.5} = \frac{4}{x}

Cross multiply

5*x = 4.5*4

5x = 18

Divide both sides by 5

x = \frac{18}{5}

x = 3.6

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2.06. In a study to estimate the proportion of residents in a certain city and its suburbs who favor the construction of a nucle
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Answer:

z=\frac{0.74-0.56}{\sqrt{0.64(1-0.64)(\frac{1}{100}+\frac{1}{125})}}=2.795  

p_v =2*P(Z>2.795)= 0.005  

So if we compare the p value and using any significance level for example \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can conclude that the proportions are different at 5% of significance.  

Step-by-step explanation:

Data given and notation  

X_{1}=74 represent the number of residents in a certain city and its suburbs who favor the construction of a nuclear power plant

X_{2}=70 represent the number of people suburban residents are in favor

n_{1}=100 sample 1 selected

n_{2}=125 sample 2 selected

p_{1}=\frac{74}{100}=0.74 represent the proportion of residents in a certain city and its suburbs who favor the construction of a nuclear power plant

p_{2}=\frac{70}{125}=0.56 represent the proportion of suburban residents are in favor

z would represent the statistic (variable of interest)  

p_v represent the value for the test (variable of interest)

Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the proportions are different, the system of hypothesis would be:  

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

We need to apply a z test to compare proportions, and the statistic is given by:  

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{74+70}{100+125}=0.64

Calculate the statistic

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.74-0.56}{\sqrt{0.64(1-0.64)(\frac{1}{100}+\frac{1}{125})}}=2.795  

Statistical decision

The significance level provided is \alpha=0.05 ,and we can calculate the p value for this test.  

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

p_v =2*P(Z>2.795)= 0.005  

So if we compare the p value and using any significance level for example \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can conclude that the proportions are different at 5% of significance.  

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