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SteveConfidence intervals of critical statistics provide a range of values within which we can reasonably estimate the true value of a population parameter based on our sample data. They are constructed by calculating the critical statistic, such as the mean or proportion, and then determining the upper and lower bounds of the interval using the standard error and a desired level of confidence, usually 95% or 99%. The confidence interval helps us understand the uncertainty around our estimates and provides a measure of the precision of our results.
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What is Confidence Intervals of Margin of Error?
The magnitude of difference between the statistic (point estimate) and the parameter (true state of nature), . This is estimated using the critical statistic and the standard error.
How do you find the confidence intervals?
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.
How hypothesis testing and the use of confidence intervals are the same?
They are related but they are NOT the same.
What is meant by the term 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.
What are the 3 confidence intervals?
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.
