Question

Which of the following errors is more serious and why?(a)Sampling error (b) Non-Sampling error

Answer 1

Answer:

Non-sampling errors are more serious than sampling errors

Explanation:

because a sampling error can be minimised by taking a larger sample. It is difficult to minimise non-sampling error, even by taking a large sample as it use of faulty means of collection of data.

Answer 2

(b) Non-sampling errors are more serious because the larger sample size cannot be minimized.

Definition of sampling and non sampling;

Sampling error- The overall data is calculated from the larger population in statistical analysis.  

Non-sampling errors- An error can be seen where the data collection differs from the actual value.

Non-sampling is more serious for the following reasons;

• Non- sampling occurs where the data collection error is random. These errors can be challenging in a survey, sample, or census.
• The information cannot be easily trusted as the higher number of errors are seen.
• The rate of bias in a study, sample, or census are seen as the data collection goes up while the systematic errors are developed.

Sampling errors are more reliable;

• The information of the sampling errors are more reliable and more systematic in survey, sample, or census.
• The data are perfectly matched and the errors increasing the sample size can be minimized easily.
• The other way of reducing the sample selection is to increase the number of observations.

Therefore, according to the observation the non-sampling errors are more serious threat in the statistical analysis. These data collection can be misused as well as the information is not reliable.