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frez [133]
3 years ago
14

According to the February 2008 Federal Trade Commission report on consumer fraud and identity theft, 23% of all complaints in 20

07 were for identity theft. In that year, Alaska had 321 complaints of identity theft out of 1,432 consumer complaints. Does this data provide enough evidence to show that Alaska had a lower proportion of identity theft than 23%?
Mathematics
1 answer:
Murljashka [212]3 years ago
5 0

Answer:

There is not enough evidence to support the claim that Alaska had a lower proportion of identity theft than 23%.  

Step-by-step explanation:

We are given the following in the question:

Sample size, n = 1432

p = 23% = 0.23

Alpha, α = 0.05

Number of theft complaints , x = 321

First, we design the null and the alternate hypothesis  

H_{0}: p = 0.23\\H_A: p < 0.23

This is a one-tailed test.  

Formula:

\hat{p} = \dfrac{x}{n} = \dfrac{321}{1432} =0.2241

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

Putting the values, we get,

z = \displaystyle\frac{0.2241-0.23}{\sqrt{\frac{0.23(1-0.23)}{1432}}} = -0.5305

Now, we calculate the p-value from the table.

P-value = 0.298

Since the p-value is greater than the significance level, we fail to reject the null hypothesis and accept the null hypothesis.

Conclusion:

Thus, there is not enough evidence to support the claim that Alaska had a lower proportion of identity theft than 23%.

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Step-by-step explanation:

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Answer:

The approximate probability is 0.1921.

Step-by-step explanation:

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The hypothesis to test whether the proportion of consumers that plan to buy a new TV screen within the next year is 0.22, is defined as:

<em>H₀</em>: The proportion of consumers that plan to buy a new TV screen within the next year is 0.22, i.e. <em>p</em> = 0.22.

<em>Hₐ</em>: The proportion of consumers that plan to buy a new TV screen within the next year is 0.22, i.e. <em>p</em> > 0.22.

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Compute the value of sample proportion as follows:

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The test statistic value is, 0.87.

Compute the <em>p</em>-value as follows:

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The <em>p-</em>value of the test is 0.1921.

Thus, the approximate probability of obtaining a sample proportion equal to or larger than the one obtained here is 0.1921.

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