b) Explain what this margin of error means. Select the correct choice below and fill in the answer box within your choice. (Round to three decimal places as needed.) OA. One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within sample proportion. B. The probability that any given adult surveyed from the population will respond "Wrong Track" is C. One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within population proportion. D. The probability that any given adult surveyed from the sample responded "Wrong Track" is of the of the reen S -0...08.

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### Educational Content on Survey Margin of Error

In a Morning Consult/Politico poll conducted in July 2020 with 1,997 registered voters, participants were asked if they believed the United States was headed in the "Right Direction" or on the "Wrong Track." The results showed that 74.9% felt things were on the wrong track, while 25.1% believed it was the right direction. The following content explains how to calculate and interpret the margin of error for such polls.

---

#### a) Calculating the Margin of Error

The margin of error (ME) for the proportion of all U.S. adults who believe things are on the wrong track was determined for a 99% confidence level:

- **Margin of Error (ME) = 0.025**

The calculation involved expressing the result to three decimal places as needed.

---

#### b) Interpreting the Margin of Error

To understand what this margin of error implies, consider the choices below. Select the appropriate meaning and complete the statement by filling in the answer box.

- **A.** One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within \[\_\_\_\] of the sample proportion.
  
- **B.** The probability that any given adult surveyed from the population will respond "Wrong Track" is \[\_\_\_\].
  
- **C.** One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within \[\_\_\_\] of the population proportion.
  
- **D.** The probability that any given adult surveyed from the sample responded "Wrong Track" is \[\_\_\_\].

When selecting the option, remember that the margin of error indicates the range within which the true population proportion is expected to fall, given the results from the sample.

---

This detailed explanation provides clarity on how statistical margins of error work in surveys and the level of confidence in interpreting such results.
Transcribed Image Text:### Educational Content on Survey Margin of Error In a Morning Consult/Politico poll conducted in July 2020 with 1,997 registered voters, participants were asked if they believed the United States was headed in the "Right Direction" or on the "Wrong Track." The results showed that 74.9% felt things were on the wrong track, while 25.1% believed it was the right direction. The following content explains how to calculate and interpret the margin of error for such polls. --- #### a) Calculating the Margin of Error The margin of error (ME) for the proportion of all U.S. adults who believe things are on the wrong track was determined for a 99% confidence level: - **Margin of Error (ME) = 0.025** The calculation involved expressing the result to three decimal places as needed. --- #### b) Interpreting the Margin of Error To understand what this margin of error implies, consider the choices below. Select the appropriate meaning and complete the statement by filling in the answer box. - **A.** One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within \[\_\_\_\] of the sample proportion. - **B.** The probability that any given adult surveyed from the population will respond "Wrong Track" is \[\_\_\_\]. - **C.** One is 99% confident that the observed proportion of adults that responded "Wrong Track" is within \[\_\_\_\] of the population proportion. - **D.** The probability that any given adult surveyed from the sample responded "Wrong Track" is \[\_\_\_\]. When selecting the option, remember that the margin of error indicates the range within which the true population proportion is expected to fall, given the results from the sample. --- This detailed explanation provides clarity on how statistical margins of error work in surveys and the level of confidence in interpreting such results.
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