To answer this question, let's break down the steps:

1. **Understanding Confidence Intervals**: A confidence interval gives a range of values that is likely to contain the population parameter with a certain level of confidence. For example, a 98% confidence interval means we are 98% confident that the interval contains the true population parameter.

2. **Effect of Confidence Level**: The confidence level determines how certain we are that the interval contains the population parameter. Higher confidence levels correspond to wider intervals because we need to cover more possible values to be more certain.

3. **Comparing 98% and 96% Confidence Levels**: When we decrease the confidence level from 98% to 96%, we are saying we need less certainty. To achieve this, we can afford to have a narrower interval because we are accepting a higher chance that the interval might not contain the population parameter.

4. **Conclusion**: Therefore, if you decrease the confidence level from 98% to 96%, the confidence interval will narrow.

So, the correct answer is: The confidence interval will narrow.

Question

To answer this question, let's break down the steps:

1. **Understanding Confidence Intervals**: A confidence interval gives a range of values that is likely to contain the population parameter with a certain level of confidence. For example, a 98% confidence interval means we are 98% confident that the interval contains the true population parameter.

2. **Effect of Confidence Level**: The confidence level determines how certain we are that the interval contains the population parameter. Higher confidence levels correspond to wider intervals because we need to cover more possible values to be more certain.

3. **Comparing 98% and 96% Confidence Levels**: When we decrease the confidence level from 98% to 96%, we are saying we need less certainty. To achieve this, we can afford to have a narrower interval because we are accepting a higher chance that the interval might not contain the population parameter.

4. **Conclusion**: Therefore, if you decrease the confidence level from 98% to 96%, the confidence interval will narrow.

So, the correct answer is: The confidence interval will narrow.

Knowee AI · Accepted Answer

To answer this question, let's break down the steps:

1. **Understanding Confidence Intervals**: A confidence interval gives a range of values that is likely to contain the population parameter with a certain level of confidence. For example, a 98% confidence interval means we are 98% confident that the interval contains the true population parameter.

2. **Effect of Confidence Level**: The confidence level determines how certain we are that the interval contains the population parameter. Higher confidence levels correspond to wider intervals because we need to cover more possible values to be more certain.

3. **Comparing 98% and 96% Confidence Levels**: When we decrease the confidence level from 98% to 96%, we are saying we need less certainty. To achieve this, we can afford to have a narrower interval because we are accepting a higher chance that the interval might not contain the population parameter.

4. **Conclusion**: Therefore, if you decrease the confidence level from 98% to 96%, the confidence interval will narrow.

So, the correct answer is: The confidence interval will narrow.

Suppose you compute a 98% confidence interval. What will happen to the confidence interval if you decrease the confidence level to 96%?The confidence interval will widen.The confidence interval will narrow.The width of the confidence interval will stay the same

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