Explore: Observed Confidence Levels (statistics)

In statistics, a confidence interval (CI) is a range of values used to estimate an unknown statistical parameter, such as a population mean. Rather than

In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series

In statistics, a confidence region is a multi-dimensional generalization of a confidence interval. For a bivariate normal distribution, it is an ellipse

the probability of the observed result given the null hypothesis and not probability of the null hypothesis given the observed result. An alternative

the confidence level γ = (1 − α) instead. This is the probability of not rejecting the null hypothesis given that it is true. Confidence levels and confidence

99% confidence for a normally distributed population. The smaller the estimated error, the larger the required sample, at a given confidence level; for

constructing a number of resamples with replacement, of the observed data set (and of equal size to the observed data set). A key result in Efron's seminal paper

experimental runs with the same factor levels. You can replicate combinations of factor levels, groups of factor level combinations, or even entire designs

observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is

parameter; i.e. 95% of confidence intervals computed at the 95% confidence level contain the true value, and likewise for other confidence levels. For example,