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OLEGan [10]
2 years ago
12

A display case of hat pins are marked 5 for $3. If Patty has $21, how many hat pins can Patty get? (assume no other taxes and fe

es)
Mathematics
1 answer:
Nonamiya [84]2 years ago
4 0
Answer: 35

Explanation: If patty has $21, and $3 is the price for 5 hat pins, then: 21/3=7, so she can buy 7 packages which cost $3 and contain 5 pins, and because the question asked the number of pins, we will multiply 7 • 5 and that equals 35
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Answer:

Step-by-step explanation:

Given that:

the sample proportion p = 0.39

sample size = 100

Then np = 39

Using normal approximation

The sampling distribution from the sample proportion is approximately normal.

Thus, mean \mu _{\hat p} = p = 0.39

The standard deviation;

\sigma = \sqrt{\dfrac{p(1-p)}{n} }

\sigma = \sqrt{\dfrac{0.39(1-0.39)}{100} }

\sigma = 0.048

The test statistics can be computed as:

Z = \dfrac{{\hat _{p}} - \mu_{_ {\hat p}} }{\sigma_{\hat p}}

Z = \dfrac{0.3 - 0.39 }{0.0488}

Z = -1. 8 4

From the z - tables;

P (\hat p \le 0.3 ) = P(z \le -1.84)

\mathbf{P (\hat p \le 0.3 ) = 0.0329}

(b)

Here;

the sample proportion = 0.39

the sample size n = 400

Since np = 400 * 0.39 = 156

Thus, using normal approximation.

From the sample proportion, the sampling distribution is approximate to the mean \mu_{\hat p} =  p = 0.39

the standard deviation \sigma_{\hat p} = \sqrt{\dfrac{p(1-p)}{n} }

\sigma_{\hat p} = \sqrt{\dfrac{0.39 (1-0.39)}{400} }

\sigma_{\hat p} =0.0244

The test statistics can be computed as:

Z = \dfrac{{\hat _{p}} - \mu_{_ {\hat p}} }{\sigma_{\hat p}}

Z = \dfrac{0.3 - 0.39 }{0.0244}

Z = -3.69

From the z - tables;

P (\hat p \le 0.3 ) = P(z \le -3.69)

\mathbf{P (\hat p \le 0.3 ) = 0.0001}

(c) The effect of the sample size on the sampling distribution is that:

As sample size builds up, the standard deviation of the sampling distribution decreases.

In addition to that, reduction in the standard deviation resulted in increases in the Z score, and the probability of having a sample proportion  that is less than 30% also decreases.

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Management at a seaside resort is publishing a brochure and wants to include a statement about the proportion of clear days duri
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Answer: B. 264

Step-by-step explanation:

Formula to calculate the sample size 'n' , if the prior estimate of the population proportion (p) is available:

n= p(1-p)(\dfrac{z}{E})^2

, where z = Critical z-value corresponds to the given confidence interval

E=  margin of error

Let p be the population proportion of clear days.

As per given , we have

Prior sample size : n= 150

Number of clear days in that sample = 117

Prior estimate of the population proportion of clear days = p=\dfrac{117}{150}

E= 0.05

The critical z-value corresponding to 95% confidence interval = z*= 1.95 (By z-table)

Then, the required sample size will be :

n= \dfrac{117}{150}(1-\dfrac{117}{150})(\dfrac{1.96}{0.05})^2

Simplify ,

n= (0.1716)(39.2)^2

n= 263.687424\approx264

Hence, the sample size necessary to construct this interval =264

Thus the correct option is B. 264

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The point (250,0) of the graph represents that the average price per ticket is $250.

Given to us

x is the price the passenger paid

f(x) is the positive percent difference

<h3>What is the correct interpretation of the point (250, 0)?</h3>

We know that a coordinate is written in the form of (x, y), therefore, the point (250, 0) represents that the price of the ticket is 250, while the 0 in the coordinate represents that there is no percentage difference. Since the point (250,0) is the mid-value of the x-axis on the graph, we can say that $250 is the average price of the ticket.

Hence, the point (250,0) of the graph represents that the average price per ticket is $250.

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