confidence interval interpretation
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.
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CI provide a slightly different estimate of statistical truth, it provide a range of the true effect observed in a study Key words: Confidence interval; p value; Precision ; |
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Interpreting the Confidence Level The sample mean will vary from sample to sample, but when the method estimate ± margin of error is used to get an interval based on each sample, C of these intervals capture the unknown population mean μ |
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IDENTIFY an appropriate point estimator and CALCULATE the value of a point estimate ✓ INTERPRET a confidence interval in context ✓ DETERMINE the |
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Probability and Confidence Intervals Learning Intentions Today we will understand: ▻ Interpreting the meaning of a confidence interval ▻ Calculating the |
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Confidence Interval Interpretation: The 95 CI for the sample mean is interpreted as a range of values which contains the true population mean with probability |