Confidence Intervals - ConfidenceIntervals :...

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Confidence Intervals There are two types of estimates for each population parameter: the point estimate and confidence  interval (CI) estimate. For both continuous variables (e.g., population mean) and dichotomous variables  (e.g., population proportion) one first computes the point estimate from a sample. Recall that sample  means and sample proportions are unbiased estimates of the corresponding population parameters. For both continuous and dichotomous variables, the  confidence interval estimate (CI)  is a range  of likely values for the population parameter based on: the point estimate, e.g., the sample mean the investigator's desired level of confidence (most commonly 95%, but any level between 0-100% can be selected) and the sampling variability or the standard error of the point estimate. Strictly speaking a 95% confidence interval means that if we were to take 100 different samples and  compute a 95% confidence interval for each sample, then approximately 95 of the 100 confidence  intervals will contain the true mean value ( μ ). In practice, however, we select one random sample and  generate one confidence interval, which may or may not contain the true mean. The observed interval  may over- or underestimate  μ . Consequently, the 95% CI is the likely range of the true, unknown  parameter. The confidence interval does not reflect the variability in the unknown parameter. Rather, it 
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