What is Confidence Interval? Confidence Interval Explained.
A confidence interval is a range of values that are calculated from sample data and is used to estimate an unknown population parameter with a certain level of confidence. It provides a measure of the uncertainty or variability associated with the estimated parameter.
Here are some key points to understand about confidence intervals:
A confidence interval is a range of values that is likely to contain the true value of a population parameter. It is constructed based on sample data and is used to estimate parameters such as population means, population proportion, or population standard deviation.
Point Estimate: A point estimate is a single value calculated from sample data that serves as an estimate of the population parameter. For example, the sample mean is often used as a point estimate of the population mean.
Confidence Level: The confidence level represents the probability or level of confidence that the confidence interval contains the true population parameter. Commonly used confidence levels are 90%, 95%, and 99%. A 95% confidence level means that if the sampling process were repeated multiple times, 95% of the resulting confidence intervals would contain the true population parameter.
The margin of Error: The margin of error is the maximum amount by which the point estimate is expected to differ from the true population parameter. It is determined by the variability of the sample data and the desired level of confidence. A narrower confidence interval indicates a smaller margin of error and a more precise estimate.
Calculation: The calculation of a confidence interval depends on the type of parameter being estimated and the distribution of the sample data. For example, when estimating the population mean with a large sample size, the confidence interval is often constructed using the sample mean and the sample standard deviation.
Interpretation: The interpretation of a confidence interval is that if the sampling process were repeated multiple times, the true population parameter would fall within the calculated interval for the specified confidence level.
Sample Size and Confidence Interval Width: The width of a confidence interval is influenced by the sample size. As the sample size increases, the confidence interval becomes narrower, indicating increased precision in estimating the population parameter.
They are widely used in inferential statistics and research studies to provide a range of plausible values for the true population parameter. The choice of confidence level depends on the desired level of certainty or risk tolerance in the estimation process.
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