Confidence analysis

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If you're seeing this message, it means we're having trouble loading external resources on our website. To log in and use all the features of Khan Academy, please enable JavaScript in your browser. Donate Login Sign up Search for courses, skills, and videos. Statistics and probability. Skill Summary Legend Opens a modal. Introduction to confidence intervals.
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Interpreting confidence levels and confidence intervals

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What are confidence intervals?

By Saul McLeod , published June 10, As the sample size increases, the range of interval values will narrow, meaning that you know that mean with much more accuracy compared with a smaller sample. We can visualize this using a normal distribution see the below graph. For example, the probability of the population mean value being between It is more or less impossible to study every single person in a population so researchers select a sample or sub-group of the population. This means that the researcher can only estimate the parameters i.
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Confidence Intervals

A confidence interval, in statistics, refers to the probability that a population parameter will fall between two set values for a certain proportion of times. Confidence intervals measure the degree of uncertainty or certainty in a sampling method. Confidence interval and confidence level are interrelated but are not exactly the same. Statisticians use confidence intervals to measure uncertainty. For example, a researcher selects different samples randomly from the same population and computes a confidence interval for each sample.
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Statisticians use a confidence interval to describe the amount of uncertainty associated with a sample estimate of a population parameter. How would you interpret this statement? This is incorrect. Like any population parameter , the population mean is a constant, not a random variable. It does not change.
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