Statistical estimates cannot be exact: there is a degree of uncertainty associated with any statistical estimate. A confidence interval is a range such that the estimated value belongs to the confidence interval with the stated probability.
They are related but they are NOT the same.
Confidence intervals represent a specific probability that the "true" mean of a data set falls within a given range. The given range is based off of the experimental mean.
There are an infinite number of confidence intervals; different disciplines and different circumstances will determine which is used. Common ones are 50% (is the event likely?), 75%, 90%, 95%, 99%, 99.5%, 99.9%, 99.99% etc.
To obtain a double interval from a normal interval in statistical analysis, you can use the command for confidence intervals, typically found in statistical software. For example, in R, you can use the t.test() function and specify the conf.level parameter as 0.95 for a normal interval, and 0.99 for a double interval. In Python, the scipy.stats library's t.interval() function can be utilized similarly to compute intervals with different confidence levels. Adjusting the confidence level effectively changes the width of the interval.
See: http://en.wikipedia.org/wiki/Confidence_interval Includes a worked out example for the confidence interval of the mean of a distribution. In general, confidence intervals are calculated from the sampling distribution of a statistic. If "n" independent random variables are summed (as in the calculation of a mean), then their sampling distribution will be the t distribution with n-1 degrees of freedom.
They are related but they are NOT the same.
confidence intervals
, the desired probabilistic level at which the obtained interval will contain the population parameter.
Esa I. Uusipaikka has written: 'Confidence intervals in generalized regression models' -- subject(s): Regression analysis, Linear models (Mathematics), Statistics, Confidence intervals
Confidence intervals represent a specific probability that the "true" mean of a data set falls within a given range. The given range is based off of the experimental mean.
No. For instance, when you calculate a 95% confidence interval for a parameter this should be taken to mean that, if you were to repeat the entire procedure of sampling from the population and calculating the confidence interval many times then the collection of confidence intervals would include the given parameter 95% of the time. And sometimes the confidence intervals would not include the given parameter.
Length
If you are a good business man then they don't.
An open interval centered about the point estimate, .
There are an infinite number of confidence intervals; different disciplines and different circumstances will determine which is used. Common ones are 50% (is the event likely?), 75%, 90%, 95%, 99%, 99.5%, 99.9%, 99.99% etc.
In a study using 9 samples, and in which the population variance is unknown, the distribution that should be used to calculate confidence intervals is
The standard deviation associated with a statistic and its sampling distribution.