The word "resampling" is pronounced /riːˈsæmpəlɪŋ/. The first syllable "re-" means "again," while the second syllable "sam-" refers to "sampling." The final syllable "-pling" represents the verb suffix used to create a present participle. In statistical analysis, resampling refers to a technique used to estimate the distribution of a statistic by sampling the data multiple times. The spelling of "resampling" suggests that it is a combination of "re-" and "sampling," with the sound of the consonants /s/, /m/, and /p/ clearly audible.
Resampling is a statistical technique or process that involves creating new samples from an existing sample to estimate or evaluate statistical parameters or test statistical hypotheses. It is used extensively in various fields, including statistics, data analysis, and computer science.
In resampling, the original sample is repeatedly sampled with replacement or without replacement to generate multiple pseudo-samples, each having the same sample size as the original. This repetition allows for the estimation of sampling distributions, confidence intervals, or p-values without assuming any specific distribution of the data.
The resampling process is commonly used when there is limited data available or when assumptions about the population distribution are uncertain. By generating multiple random resamples, the technique allows for the calculation of various statistics or models to assess the uncertainty associated with the estimators.
Some popular resampling methods include bootstrap resampling, where samples are drawn with replacement, and permutation resampling (also known as randomization tests), where samples are obtained by randomly permuting the observations. These methods help to address issues such as bias, variance, and hypothesis testing when traditional approaches may not be applicable or reliable.
Overall, resampling is a powerful tool in statistics that enables researchers to make inferences about population parameters, test hypotheses, and evaluate the performance of statistical models by repeatedly sampling from an existing sample.
The word "resampling" is derived from two base words: "re" and "sampling".
The prefix "re-" is of Latin origin and means "again" or "back". It is commonly used to indicate repetition or returning to a previous state or action.
"Sampling" comes from the verb "sample", which originates from the Middle English word "sampler" and the Old French word "essample". It traces back to the Latin word "exemplum", meaning "example" or "pattern". In its original sense, "sample" referred to taking a small portion or specimen to represent the whole.
Therefore, "resampling" combines the prefix "re-" with "sampling" to indicate the action of sampling something again or repeatedly.