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When you calculate a statistic the result is not going to be perfectly accurate because of random errors in your observations. You therefore can give the result as one value along with a confidence interval (CI) around it.

There are two interpretations of a CI. One interpretation is that you can be confident, with the stated level of confidence, that the true value of your statistic lies within the CI.

The other interpretation is that if you repeated your experiment then, for the stated percentage of cases, the statistic would lie within the CI.

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Q: What is a confidence interval in statistics?
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Related questions

How do you calculate confidence interval?

Confidence intervals may be calculated for any statistics, but the most common statistics for which CI's are computed are mean, proportion and standard deviation. I have include a link, which contains a worked out example for the confidence interval of a mean.


Which statistics are used to construct a confidence interval?

The parameters of the underlying distribution, plus the standard error of observation.


In a confidence interval what information does the margin of error provide?

The confidence interval consists of a central value and a margin of error around that value. If it is an X% confidence interval then there is a X% probability that the true value of the statistic in question lies inside the interval. Another way of looking at it is that if you took repeated samples and calculated the test statistic each time, you should expect X% of the test statistics to fall within the confidence interval.


Why confidence interval useful?

Why confidence interval is useful


What is confidence intervals in statistics?

The Confidence Interval is a particular type of measurement that estimates a population's parameter. Usually, a confidence interval correlates with a percentage. The certain percentage represents how many of the same type of sample will include the true mean. Therefore, we would be a certain percent confident that the interval contains the true mean.


What happens to the confidence interval if you increase the confidence level?

The confidence interval becomes wider.


When population distribution is right skewed is the interval still valid?

You probably mean the confidence interval. When you construct a confidence interval it has a percentage coverage that is based on assumptions about the population distribution. If the population distribution is skewed there is reason to believe that (a) the statistics upon which the interval are based (namely the mean and standard deviation) might well be biased, and (b) the confidence interval will not accurately cover the population value as accurately or symmetrically as expected.


What Confidence interval is 0.05 alpha?

how are alpha and confidence interval related


The width of a confidence interval is equal to twice the value of the margin of error?

No. The width of the confidence interval depends on the confidence level. The width of the confidence interval increases as the degree of confidence demanded from the statistical test increases.


What happens to the confidence interval as the mean decreases?

The confidence interval is not directly related to the mean.


What happens to the confidence interval if you increase the sample size?

The confidence interval becomes smaller.


Is a 95 percent confidence interval for a mean wider than a 99 percent confidence interval?

No, it is not. A 99% confidence interval would be wider. Best regards, NS