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Sampling and Non-Sampling Errors Video Lecture | Economics Class 11 - Commerce

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FAQs on Sampling and Non-Sampling Errors Video Lecture - Economics Class 11 - Commerce

1. What is the difference between sampling and non-sampling errors?
Answer: Sampling errors occur when the sample taken from a population is not representative of the entire population, while non-sampling errors are errors that occur during data collection, processing, or analysis that are not related to the sampling process.
2. How can sampling errors be reduced in a research study?
Answer: Sampling errors can be reduced by increasing the sample size, using random sampling techniques, and ensuring that the sample is representative of the population being studied.
3. What are some common examples of non-sampling errors in research studies?
Answer: Common examples of non-sampling errors include measurement errors, data entry errors, processing errors, and non-response errors.
4. How do non-sampling errors impact the validity of research findings?
Answer: Non-sampling errors can lead to biased results, inaccurate conclusions, and reduced validity of research findings. It is important to minimize non-sampling errors to ensure the reliability of the study.
5. Can both sampling and non-sampling errors occur simultaneously in a research study?
Answer: Yes, it is possible for both sampling and non-sampling errors to occur simultaneously in a research study. Researchers should be aware of the different types of errors and take steps to minimize their impact on the study results.
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