Question 60

Lowering the significance level increases the level of confidence.

By lowering the significance level, the researcher effectively increases the confidence level of the interval, allowing for a wider range that is more likely to contain the population parameter of interest.

A) Lower the significance level

This option is correct because lowering the significance level (for example, from 0.05 to 0.01) increases the corresponding confidence level (from 95% to 99%). A lower significance level indicates that the researcher is willing to accept a smaller risk of making a Type I error, thereby enhancing the reliability of the interval estimate.

B) Use a different estimator

This option is incorrect because changing the estimator does not inherently affect the level of confidence of the confidence interval. The confidence level is determined by the significance level, not the choice of estimator used to calculate the interval.

C) Raise the significance level

This option is incorrect as raising the significance level (for example, from 0.05 to 0.10) decreases the confidence level (from 95% to 90%). This would result in a less reliable interval that is less likely to contain the true population parameter.

D) Collect another sample

This option is incorrect in the context of increasing the level of confidence. While collecting another sample can provide more data and potentially lead to a more accurate estimate, it does not directly affect the confidence level associated with the confidence interval calculated from the original sample.

Conclusion

Lowering the significance level is the definitive method to increase the level of confidence in a confidence interval, as it directly influences the confidence level associated with the interval. All other options do not effectively change the confidence level and thus fail to meet the requirement of the question.