Choose Index below for a list of all words and phrases defined in this glossary.

Confidence Level

index | Index

Confidence Level - definitions

Confidence level - The degree of certainty, expressed as a percentage, of being sure that the value for the mean of a population is within a specific range of values around the mean of a sample. For example, a 95 percent confidence level indicates that one is 95 percent sure that the estimate of the mean is within a desired precision or range of values called a confidence interval. Stated another way, a 95 percent confidence level means that out of 100 samples from the same population, the mean of the population is expected to be contained within the confidence interval in 95 of the 100 samples.

[Category=Data Quality ]

Source: Larry English, External , 17-Jan-2009 12:59

These advertisers support this free service

Confidence Level - Statistically valid measure of how often, in one hundred attempts, test results can be expected to be within given limits. Confidence level is based not on the number of pieces mailed, but on the number of responses received.

[Category=Database Marketing ]

Source: Postcom, 21 February 2010 11:13:27, External

Confidence level - suppression - Matching against a preset number of industry suppression files to set a confidence level to suit your business. For example, requiring a match against 3 different files to permanently suppress someone from your database.

[Category=Database Marketing ]

Source: DBG, 02 May 2011 08:07:00, External

confidence level - [statistics] In a statistical test, the risk, expressed as a percentage, that the null hypothesis will be incorrectly rejected because of sampling error when the null hypothesis is true. For example, a confidence level of 95 percent means that if the same test were performed 100 times on 100 different samples, the null hypothesis would be incorrectly rejected five times.

[Category=Geospatial ]

Source: esri, 01 March 2012 09:26:19, External 

Data Quality Glossary.  A free resource from GRC Data Intelligence. For comments, questions or feedback: