Statistics - (Degree|Level) of confidence

Thomas Bayes


Degree of confidence represents the probability that the confidence interval captures the true population parameter.

With a degree of confidence of 95%, you have 95% confidence that the true population parameters will be in the confidence interval.

95% is the standard.

If you want 95% confidence that you're capturing the true population parameters, you may sometimes have to report a really wide interval.

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Thomas Bayes
Statistics - (Confidence|likelihood) (Prediction probabilities|Probability classification)

Prediction probabilities are also known as: confidence (How confident can I be of this prediction?). or likelihood: (How likely is this prediction to be true?) They gives the probability of a predicted...
Thomas Bayes
Statistics - Confidence Interval

The definition of a confidence interval says that under repeated experiments 95% of the time this confidence interval will contain the true statistic (mean, ...). if we started the whole experiment over...

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