Final answer:
option c,To reduce non sampling error, improving data collection techniques is the most effective strategy, addressing factors unrelated to the sample size, such as biased sampling methods and accurate data handling.
Step-by-step explanation:
The best way to reduce systematic error, also known as nonsampling error, is to improve data collection techniques. Systematic errors are caused by factors that do not relate to the process of sampling itself, such as defective counting devices or biased sampling methods. Improving data collection can include better training for researchers, improved survey instruments, and meticulous data handling procedures. Offering incentives to respondents or substituting houses in a survey can potentially introduce bias, and merely increasing sample size addresses sampling errors rather than nonsampling errors. Therefore, a focus on data collection quality is essential in reducing systematic error.
To reduce systematic error or nonsampling error, the best approach is to improve data collection techniques. Nonsampling errors are errors not related to the sampling process, such as errors in data collection or data entry. By refining data collection techniques, such as using standardized protocols or training data collectors on proper methods, the likelihood of these errors can be minimized.