Confidence Interval

Confidence intervals communicate how accurate an estimate of a parameter of the population is likely to be. A confidence interval is the mean of your estimate plus and minus the variation in that estimate. This is the range of values you expect your estimate to fall between if you redo your test, within a certain level of confidence. Confidence, in statistics, is another way to describe probability. A confidence interval is a range of estimates for an unknown parameter. A confidence interval is computed at a designated confidence level. Factors affecting the width of the CI include the confidence level, the sample size, and the variability in the sample. All else being the same, a larger sample would produce a narrower confidence interval. Likewise, greater variability in the sample produces a wider confidence interval, and a higher confidence level would demand a wider confidence interval. This video explains the importance and ways of calculating the confidence interval in experiment research settings. 1. Introduction 00:32 2. The 3 Rs 02:53 3. Confidence Interval Calculation 11:32 4. Robustness Check 17:17 5. Take Away 21:19