A handpicked collection of wild, absurd, and laugh-out-loud profanity definitions and pronunciations — for your chaotic curiosity, twisted education, and pure entertainment.

Definition: Bootstrapping, also known as bootstrap estimation, is a method of estimating parameters in statistical models. It involves starting with an initial estimate and then using a random sample from the data set to iteratively update the estimate until convergence is achieved. In simpler terms, bootstrapping is like taking many samples (or "bootstraps") from your original dataset and averaging them together to get an average. This method helps in obtaining a more accurate estimate of parameters than if you were to use all of

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Definition: Bootstraps, also known as bootstrap confidence intervals or bootstrapped standard errors, are statistical methods used to estimate the variability of a sample statistic. They are particularly useful when the population from which the sample was drawn is not normally distributed and there are multiple samples being compared. In simple terms, "bootstraps" refer to the process of drawing a random sample from the original data set and then computing an interval estimate for the mean of that sample. These intervals are used to make inferences

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