You may need to use the appropriate appendix table or technology to answer this question. A survey asked senior executives at large corporations their opinions about the economic outlook for the future. One question was, "Do you think that there will be an increase in the number of full-time employees at your company over the next 12 months?" In the current survey, 228 of 400 executives answered Yes, while in a previous year survey, 176 of 400 executives had answered Yes. Provide a 95% confidence interval estimate for the difference between the proportions at the two points in time. (Use current year previous year. Round your answer to four decimal places.) to What is your interpretation of the interval estimate? The 95% confidence interval ---Select--- ✓zero. This suggests that the proportion of executives who are predicting an increase in full- than the proportion of executives who were predicting an increase in full-time jobs for the time jobs for the current year is ---Select--- previous year.

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**Confidence Interval for Proportions of Senior Executives' Predictions on Full-Time Employment**

You may need to use the appropriate [appendix table](#) or [technology](#) to answer this question.

A survey asked senior executives at large corporations their opinions about the economic outlook for the future. One question was, "Do you think that there will be an increase in the number of full-time employees at your company over the next 12 months?" In the current survey, **228 of 400 executives** answered Yes, while in a previous year survey, **176 of 400 executives** had answered Yes. Provide a **95% confidence interval** estimate for the difference between the proportions at the two points in time. (Use current year – previous year. Round your answer to four decimal places.)

**Confidence Interval:**
\[ \_\_\_\_\_\_ \text{ to } \_\_\_\_\_\_ \]

**Interpretation of the Interval Estimate:**

The 95% confidence interval **----Select----** zero. This suggests that the proportion of executives who are predicting an increase in full-time jobs for the current year is **----Select----** than the proportion of executives who were predicting an increase in full-time jobs for the previous year.

**Note:** 
- Ensure to calculate the confidence interval accurately using the formula for the difference in proportions.
- The parameters are clearly outlined as:
  - Current year proportion (\( p_1 \) for 2023) = \( \frac{228}{400} \)
  - Previous year proportion (\( p_2 \) for 2022) = \( \frac{176}{400} \)
- When interpreting, consider whether the interval includes zero or not, which indicates whether there is a significant difference in proportions between the two years.
Transcribed Image Text:**Confidence Interval for Proportions of Senior Executives' Predictions on Full-Time Employment** You may need to use the appropriate [appendix table](#) or [technology](#) to answer this question. A survey asked senior executives at large corporations their opinions about the economic outlook for the future. One question was, "Do you think that there will be an increase in the number of full-time employees at your company over the next 12 months?" In the current survey, **228 of 400 executives** answered Yes, while in a previous year survey, **176 of 400 executives** had answered Yes. Provide a **95% confidence interval** estimate for the difference between the proportions at the two points in time. (Use current year – previous year. Round your answer to four decimal places.) **Confidence Interval:** \[ \_\_\_\_\_\_ \text{ to } \_\_\_\_\_\_ \] **Interpretation of the Interval Estimate:** The 95% confidence interval **----Select----** zero. This suggests that the proportion of executives who are predicting an increase in full-time jobs for the current year is **----Select----** than the proportion of executives who were predicting an increase in full-time jobs for the previous year. **Note:** - Ensure to calculate the confidence interval accurately using the formula for the difference in proportions. - The parameters are clearly outlined as: - Current year proportion (\( p_1 \) for 2023) = \( \frac{228}{400} \) - Previous year proportion (\( p_2 \) for 2022) = \( \frac{176}{400} \) - When interpreting, consider whether the interval includes zero or not, which indicates whether there is a significant difference in proportions between the two years.
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