Question

The measurement of sampling error is usually called:

• A. Significance level
• B. Confidence level
• C. Precision of sampling plan
• D. Validation of data

Hint:

Sampling error decreases with an increase in sample size.
Precision is inversely related to sampling error.
Confidence level is linked to sampling error but is not the measurement of it.

Answer 1

The Correct Option is C

Step 1: Understanding the Concept:
Sampling error is the difference between a sample statistic and the true population parameter.
It arises due to the randomness of sampling.

Step 2: Key Approach:
Identify the term that measures or quantifies sampling error.

Step 3: Detailed Explanation:
The measurement of sampling error is known as the precision of the sampling plan.
Precision indicates how close the sample estimates are to the true population values.
A higher precision means a smaller sampling error.
Significance level refers to the probability of rejecting a true null hypothesis in hypothesis testing.
Confidence level is the probability that a parameter falls within a specified range.
Validation of data refers to ensuring data quality and correctness.
Thus, precision directly relates to the magnitude of sampling error.
It is determined by sample size and sampling design.