00000 the confidence interval? Both the margin of error and the width would increase. The margin of error would increase and the width would decrease The margin of error would decrease and the width would increase. Both the margin of error and the width would decrease. Neither the margin of error nor the width would be affected.

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### Understanding Confidence Intervals

In the context of statistical analysis, a confidence interval is a range of values used to estimate a true population parameter. This range is defined by a specified level of confidence, such as 99% or 90%. The margin of error and the width of the confidence interval are crucial components in understanding the reliability and precision of this estimate.

#### Question Analysis

The question presented reads:
*In question above a 99% confidence interval was computed. If the confidence level were decreased to 90%, what impact would this have on the margin of error and width of the confidence interval?*

### Answer Choices:

1. **Both the margin of error and the width would increase.**
2. **The margin of error would increase and the width would decrease.**
3. **The margin of error would decrease and the width would increase.**
4. **Both the margin of error and the width would decrease.**
5. **Neither the margin of error nor the width would be affected.**

### Explanation

When we decrease the confidence level from 99% to 90%, the following changes are observed:

- **Margin of Error**: The margin of error will **decrease**. This is because a lower confidence level results in a smaller z-score (or t-score), which in turn reduces the margin of error.
- **Width of the Confidence Interval**: The width of the confidence interval will **decrease**. A reduced margin of error leads to a narrower interval, indicating less uncertainty in the estimate.

Thus, the correct answer to the question is:
*Both the margin of error and the width would decrease.*

Understanding these concepts is crucial for interpreting the precision and reliability of statistical estimates in various fields of research.
Transcribed Image Text:### Understanding Confidence Intervals In the context of statistical analysis, a confidence interval is a range of values used to estimate a true population parameter. This range is defined by a specified level of confidence, such as 99% or 90%. The margin of error and the width of the confidence interval are crucial components in understanding the reliability and precision of this estimate. #### Question Analysis The question presented reads: *In question above a 99% confidence interval was computed. If the confidence level were decreased to 90%, what impact would this have on the margin of error and width of the confidence interval?* ### Answer Choices: 1. **Both the margin of error and the width would increase.** 2. **The margin of error would increase and the width would decrease.** 3. **The margin of error would decrease and the width would increase.** 4. **Both the margin of error and the width would decrease.** 5. **Neither the margin of error nor the width would be affected.** ### Explanation When we decrease the confidence level from 99% to 90%, the following changes are observed: - **Margin of Error**: The margin of error will **decrease**. This is because a lower confidence level results in a smaller z-score (or t-score), which in turn reduces the margin of error. - **Width of the Confidence Interval**: The width of the confidence interval will **decrease**. A reduced margin of error leads to a narrower interval, indicating less uncertainty in the estimate. Thus, the correct answer to the question is: *Both the margin of error and the width would decrease.* Understanding these concepts is crucial for interpreting the precision and reliability of statistical estimates in various fields of research.
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