confidence interval interpretation


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  • Strictly speaking, what is the best interpretation of a 95% confidence interval for the mean? If repeated samples were taken and the 95% confidence interval was computed for each sample, 95% of the intervals would contain the population mean.

  • What do confidence intervals tell us?

    Why have confidence intervals? Confidence intervals are one way to represent how "good" an estimate is; the larger a 90% confidence interval for a particular estimate, the more caution is required when using the estimate.
    Confidence intervals are an important reminder of the limitations of the estimates.

  • What does 95% confidence interval score mean?

    This means that there is a 95% probability that the confidence interval will contain the true population mean.
    Thus, P( [sample mean] - margin of error < μ < [sample mean] + margin of error) = 0.95.

  • How do you interpret a 95% confidence interval?

    Example: IQ Scores
    These data were used to construct a 95% confidence interval of [96.656, 106.422].
    Interpretation: The correct interpretation of this confidence interval is that we are 95% confident that the mean IQ score in the population of all students at this school is between 96.656 and 106.422.

  • The confidence interval describes the uncertainty inherent in this estimate, and describes a range of values within which we can be reasonably sure that the true effect actually lies. If the confidence interval is relatively narrow (e.g. 0.70 to 0.80), the effect size is known precisely.
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