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Evidence-based management and development planning relies on official statistics. There are some obstacles that make it impossible to do a single-mode survey. These obstacles are the sampling frame, time, budget, and accuracy of measurement of each mode. Always we can not use a single-mode survey because of these factors. So we need to use other data collection methods to overcome these obstacles. This method is called the mixed-mode survey, which is a combination of several modes. In this article, we show that mixed-mode surveys can produce more accurate official statistics than single-mode surveys.

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Nonrespose is a source of error in the survey results and National statistical organizations are always looking for ways to
control and reduce it. Predicting nonrespons sampling units in the survey before conducting the survey is one of the solutions
that can help a lot in reducing and treating the survey nonresponse. Recent advances in technology and the facilitation of
complex calculations have made it possible to apply machine learning methods, such as regression and classification trees
or support vector machines, to many issues, including predicting the nonresponse of sampling units in statistics. . In this
article, while reviewing the above methods, we will predict the nonresponse sampling units in a establishment survey using
them and we will show that the combination of the above methods is more accurate in predicting the correct nonresponse
than any of the methods.