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Lisa [10]
2 years ago
13

there were 936,795 bankruptcy filings in 2018. If there were 310,061 chapter 13 filings, what percent were not chapter 13

Mathematics
1 answer:
Marat540 [252]2 years ago
4 0

66.90% of the total bankruptcy fillings are not chapter 13 fillings.

What is bankruptcy?

This is a situation where the management of a company declares that it could no longer pay its debt obligations as it does have the cash resources to do so.

In this case, the total number of bankruptcy fillings is 936,795, out of which 310,061 are chapter 13 filings

fillings that were not chapter 13=936,795-310,061

fillings that were not chapter 13=626,734

fillings that were not chapter 13 as % of total fillings=626,734/936,795

fillings that were not chapter 13 as % of total fillings=66.90%

Learn more on bankruptcy on:brainly.com/question/4418659

#SPJ1

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Step-by-step explanation:

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A random sample of 200 shoppers at a local grocery store found that 135 of the 200 sampled
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Using the z-distribution, as we are working with a proportion, it is found that samples of 937 should be taken.

<h3>What is a confidence interval of proportions?</h3>

A confidence interval of proportions is given by:

\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}

In which:

  • \pi is the sample proportion.
  • z is the critical value.
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The margin of error is given by:

M = z\sqrt{\frac{\pi(1-\pi)}{n}}

In this problem, we have that:

  • The estimate is of \pi = 0.675.
  • The margin of error is of M = 0.03.
  • 95% confidence level, hence\alpha = 0.95, z is the value of Z that has a p-value of \frac{1+0.95}{2} = 0.975, so z = 1.96.

Then, we solve for n to find the minimum sample size.

M = z\sqrt{\frac{\pi(1-\pi)}{n}}

0.03 = 1.96\sqrt{\frac{0.675(0.325)}{n}}

0.03\sqrt{n} = 1.96\sqrt{0.675(0.325)}

\sqrt{n} = \frac{1.96\sqrt{0.675(0.325)}}{0.03}

(\sqrt{n})^2 = \left(\frac{1.96\sqrt{0.675(0.325)}}{0.03}\right)^2

n = 936.4

Rounding up, it is found that samples of 937 should be taken.

More can be learned about the z-distribution at brainly.com/question/25890103

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