These included methods of sequential analysis and sampling inspection. These are selected by a combination of computer analysis of return information and random sampling. Includes tools to analyze the data produced by a sampling run. It can also be explained with reference to the sampling and Nyquist frequency. The MPC combines sampling and sequencing functions. Then simple random sampling or systematic sampling is applied within each stratum. There has been some work done in Sampling algorithms for big data. Several efficient algorithms for simple random sampling have been developed. The uniform distribution is useful for sampling from arbitrary distributions. Incorrect assumptions of 'simple' random sampling can invalidate statistical inference. Its cornerstone is the calculation of probability density functions for sampling statistics. The statement also relies on the inference that the sampling was random. Other key techniques in this field are negative sampling and word embedding. There is always a trade-off between this method of quick sampling and accuracy. The variance arising from the binomial sampling is conspicuously present.