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.