Six Sigma Tutorial -> Confidence Intervals

Confidence Intervals Contd.

The width of the confidence interval, in our case 24-20=4 is a measure that is directly proportional to the precision.

Consider this scenario..

What if Acme Nelson's survey predicted that John Doe will get 22% plus or minus 20% vote. In other words Acme is saying John Doe will get between 2% and 42% of the vote.

How good is this number? Even a monkey can predict that. This is a very wide confidence range and in order to reduce the Confidence Interval, Acme needs to collect more samples.

Confidence Limits

Confidence limits are the lower and upper boundaries of a confidence interval.

In our Acme example, the limits were 20 and 24.

Confidence Level

The confidence level is the probability value attached to a given confidence interval. It can be expressed as a percentage (in our example it is 95%) or a number (0.95).

Confidence Interval for a Mean

A confidence interval for a mean is a range of values within which the mean (unknown population parameter) may lie.

Examples of Confidence Interval for a Mean

• A Web master who wishes to estimate her mean daily hits on a certain webpage.
• An environmental health and safety officer who wants to estimate the mean monthly spills.

Confidence Interval for the Difference Between Two Means

A confidence interval for the difference between two means specifies a range of values within which the difference between the means of the two populations may lie.

Examples of Confidence Interval for the Difference Between Two Means

• A Web master who wishes to estimate her difference in mean daily visitors between two websites.
• An environmental health and safety officer who wants to estimate the difference in mean monthly spills between two production sites.

Confidence Intervals Summary

Confidence intervals are very crucial to Six Sigma. Confidence intervals provide crucial information as they give us a range of possible values and attach a confidence level to the interval.