Title: Confidence Interval (CI)
Headings: Confidence Interval
Confidence Interval
Sample Size
Point Estimate
CI = POINT ESTIMATE +/- (Reliability Factor) (Standard Error)
Confidence Interval for the MEAN
= sample mean +/- (confidence factor) (measure of variability)
Confidence Interval MEAN with KNOWN σ
EXAMPLE:
What does this tell us?
Confidence Interval MEAN with UNKNOWN σ
EXAMPLE:
What does this tell us?
Excel - Confidence Interval for MEAN
Confidence Interval for the STANDARD DEVIATION
Confidence Interval for PROPORTIONS
Confidence Interval for CAPABILITY
Confidence Interval Download
Confidence Interval Roadmap
Asymmetric Confidence Interval
Relationship with Margin of Error (ME)

Content: Confidence Interval = CI = 1 - alpha risk
(1 - alpha-risk) is called the probability content or level of confidence. Alpha-risk is known as the significance level; the probability of being making an incorrect decision, in other words, being wrong. A specified value of the CI signifies that probability of the interval containing the population parameter, and that there is an alpha-risk (1-CI) that the population parameter is not contained within the interval. CI's are applied in statistical test for means, standard deviations, proportions, capability indices, regression analysis, and upper/lower control limits on control charts. In regression analysis, the CI is based on a provided value of X for a given level of confidence. This CI is likely to contain the true best fit line. There are three factors that impact the confidence interval: Sample size
Population size
Percentage
Sample Size
CI's are used when you are unable to capture and analyze an entire population (census) and the sample (statistics) to infer statements about a population. The larger your sample size, the more confidence one can be that their answers represent the population.