The difference between what is true and the results of findings in a research study is referred to as error.
The accuracy of a research report depends on several interrelated factors, including the purpose of the study must be clearly articulated, the research plan must be correctly executed, the correct sampling procedures and techniques must be used, and the data must be collected and analyzed correctly.
An error anywhere can undermine the good design, the sampling techniques used, and the design of the questionnaire. Apart from conceptual differences, many kinds of errors can help explain differences in the output of programs that generate income data.
They are often categorized into two broad types he of sampling errors and non-sampling errors. Sampling error occurs when researchers collect information from respondents who differ in some way from the actual population of interest. Non-sampling errors are numerous, ubiquitous in nature, and highly random.
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