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Interval
Estimation For
Means Interval estimation involves using sample data to determine a range (interval) that, at an established level of confidence, will contain the mean of the population. Steps 2. Use either z distribution (if n>120) or t distribution (for all sizes of n). 3. Use the appropriate table to find the critical value for a 2-tailed test 4. Multiple hypotheses can be compared with the estimated interval for the population to determine their significance. In other words, differing values of population means can be compared with the interval estimation to determine if the hypothesized population means fall within the region of rejection. 
where
CV = critical value (consult distribution table for df=n-1 and chosen alpha-- commonly .05)
 Example
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= sample mean 
(when
using the t distribution) 
(when
using the z distribution; assumes large sample size)