Chapter 5. Understanding Confidence Intervals
Understanding confidence intervals (CIs) is a fundamental aspect of statistical analysis that provides valuable insights into the reliability and precision of data. A confidence interval is a range of values within which we can reasonably expect the true population parameter to lie, based on a sample from that population. It serves as a statistical tool to quantify the uncertainty inherent in inferential statistics, allowing researchers and decision makers to make informed conclusions about population parameters. A solid grasp of confidence intervals empowers individuals to interpret study results more effectively, make informed decisions, and communicate the degree of certainty or uncertainty associated with their findings.
In this chapter, you will learn about confidence intervals, what they mean, how to interpret them, and how to implement them into your work. There are different types of confidence intervals, but this chapter will cover only average and median two-tailed confidence intervals.
What Is a Confidence Interval?
A confidence interval is a range of values that you expect your estimate to fall between a certain percentage of the time if you were to run your experiment again or resample the population. Confidence intervals normally contain the average or median of the estimate as a central point and a plus and minus variation from that center point. This plus or minus variation is your confidence interval range.
A confidence ...
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