Confidence Interval Formulas

Decision Tree for selecting What Formula to use:


Six Sigma Z Confidence Intervals for Means

Z Confidence Interval for Means applies to a mean from a normal distribution of variable data. Use the normal distribution for the confidence interval for a mean if the sample size n is relatively large (= 30), and s is known. The confidence interval (C.I.) includes the shaded area under the curve in between the critical values, excluding the tail areas (the a risk). The entire curve represents the most likely distribution of population means, given the sample’s size, mean, and the population’s standard deviation.

Six-Sigma-Z-Confidence-Interval-Means-Chart Six-Sigma-Z-Confidence-Interval-Means-Formula1

Here we are making an assumption that the underlying data we are working with is distributed like the bell curve shown. The most common confidence interval used in industry is probably the 95% confidence interval. If we were to use its formula on many sets of data from the population, then 95% of the intervals would contain the unknown population mean that we are trying to estimate. And 5% of the intervals would not contain the population mean. 2.5% of the time, the interval would be low, and 2.5% of the time, the interval would be too high. The probability is 95% that the interval contains the population parameter. The 95% value is the confidence coefficient, or the degree of confidence. The end points of the interval are called the confidence limits. In the graphic on the top, the endpoints are defined by


<<< Confidence LimitsZ Confidence Interval for Means – Example >>>
Learn all the Six Sigma Concepts explained here plus many more in just 4 weeks. Buy our Six Sigma Handbook for only 19.95$ and learn Six Sigma in just 4 weeks. This handbook comes with 4 weekly modules. Eeach module has around 250 powerpoint slides containing six sigma concepts, examples and quizzes.
Copyright 2005-2016 KnowledgeHills. Privacy Policy. Contact .