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Wald Interval
In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success–failure experiments (Bernoulli trial, Bernoulli trials). In other words, a binomial proportion confidence interval is an interval estimate of a success probability ''p'' when only the number of experiments ''n'' and the number of successes ''nS'' are known. There are several formulas for a binomial confidence interval, but all of them rely on the assumption of a binomial distribution. In general, a binomial distribution applies when an experiment is repeated a fixed number of times, each trial of the experiment has two possible outcomes (success and failure), the probability of success is the same for each trial, and the trials are statistically independent. Because the binomial distribution is a discrete probability distribution (i.e., not continuous) and difficult to calculate for large numbers of trials, a variety o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Michael Short (engineer)
Michael Short (born August 1975) is Professor of Control Engineering and Systems Informatics and leads the Centre for Sustainable Engineering at Teesside University in the UK. He received a BEng (Electrical and Electronic Engineering) in 1999 and a PhD (Robotics) in 2003 from the University of Sunderland. In 2012 he was also awarded a PGCHE from Teesside University. He was previously at the University of Leicester until 2009, and was made Reader (Professor) in January 2015 and full (Chair) Professor (by Research) in August 2020. Michael is also a time-served automation and process control engineer, with eight years' industrial experience. Michael is a full member of the Institute of Engineering and Technology ( MIET) since 1999, a fellow of the Higher Education Academy (FHEA) since 2012 and a full member of the Institute of Electrical and Electronics Engineers ( MIEEE), and he also sits on the IEEE Industrial Electronics Society Technical Committee on Factory Automation (TCFA) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Clopper-Pearson Interval
In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success–failure experiments (Bernoulli trial, Bernoulli trials). In other words, a binomial proportion confidence interval is an interval estimate of a success probability ''p'' when only the number of experiments ''n'' and the number of successes ''nS'' are known. There are several formulas for a binomial confidence interval, but all of them rely on the assumption of a binomial distribution. In general, a binomial distribution applies when an experiment is repeated a fixed number of times, each trial of the experiment has two possible outcomes (success and failure), the probability of success is the same for each trial, and the trials are statistically independent. Because the binomial distribution is a discrete probability distribution (i.e., not continuous) and difficult to calculate for large numbers of trials, a variety o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
