A 99 percent confidence interval would be wider than a 95 percent confidence interval (for example, plus or minus 4.5 percent instead of 3.5 percent). A 90 percent confidence interval would be narrower (plus or minus 2.5 percent, for example).
Consequently, what is the effect of increasing the level of confidence on the width of the interval?
Increasing the sample size decreases the width of confidence intervals, because it decreases the standard error. c) The statement, "the 95% confidence interval for the population mean is (350, 400)", is equivalent to the statement, "there is a 95% probability that the population mean is between 350 and 400".
What is a good 95% confidence interval?
If repeated samples were taken and the 95% confidence interval was computed for each sample, 95% of the intervals would contain the population mean. A 95% confidence interval has a 0.95 probability of containing the population mean. 95% of the population distribution is contained in the confidence interval.
How can the width of a confidence interval be reduced?
- Increase the sample size. Often, the most practical way to decrease the margin of error is to increase the sample size.
- Reduce variability. The less that your data varies, the more precisely you can estimate a population parameter.
- Use a one-sided confidence interval.
- Lower the confidence level.