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With the application of probability sampling in the 1930s, surveys became a standard tool for empirical research in social sciences, marketing, and official statistics. [1] The methods involved in survey data collection are any of a number of ways in which data can be collected for a statistical survey. These are methods that are used to ...
Focus groups first started in the 1940s as a research method in the context of market research concerning radio soap operas. [9] During the Second World War, Robert K. Merton set out to analyze the effectiveness of propaganda with the use of focus groups. [10]
Survey methodology is "the study of survey methods". [1] As a field of applied statistics concentrating on human-research surveys, survey methodology studies the sampling of individual units from a population and associated techniques of survey data collection, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys.
The Italian AGRIT survey has explored different approaches, comparing segment and point methods. [7] The Joint Research Centre of the EC has conducted a large number of studies on area sampling frame methodology and area frame surveys for agricultural, forestry, environmental and human settlement studies. [8] [9]
Bias in surveys is undesirable, but often unavoidable. The major types of bias that may occur in the sampling process are: Non-response bias: When individuals or households selected in the survey sample cannot or will not complete the survey there is the potential for bias to result from this non-response.
In social science research, snowball sampling is a similar technique, where existing study subjects are used to recruit more subjects into the sample. Some variants of snowball sampling, such as respondent driven sampling, allow calculation of selection probabilities and are probability sampling methods under certain conditions.
This method can be used in health and social sciences. For instance, researchers used two-stage cluster sampling to generate a representative sample of the Iraqi population to conduct mortality surveys. [8] Sampling in this method can be quicker and more reliable than other methods, which is why this method is now used frequently.
A variety of data re-sampling techniques are implemented in the imbalanced-learn package [1] compatible with the scikit-learn Python library. The re-sampling techniques are implemented in four different categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and ensembling sampling.