Lower Confidence Bound

Lower Confidence Bound (LCB) is a statistical method used in Data Science to estimate the lower limit of a confidence interval for a given sample size and level of confidence. It is used to determine the minimum value of a parameter with a certain level of confidence. LCB is commonly used in A/B testing to determine the minimum difference between two groups that is statistically significant. The LCB is calculated by subtracting the margin of error from the sample mean. The margin of error is calculated using the standard error of the mean and the t-distribution. The LCB is useful in situations where the cost of a false negative is high, such as in medical testing or quality control. By setting a lower confidence bound, we can be more certain that the true value of the parameter is above a certain threshold.
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