Random Sampling Statistics Example 3
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Example 3
mediumA factory produces 10,000 widgets per day. A quality inspector wants to check 100 widgets. She takes every 100th widget off the production line, starting with widget number 37 (chosen randomly). What type of sampling is this? What potential problem could arise?
Solution
- 1 Step 1: This is systematic sampling — selecting every -th item (every 100th widget) after a random start (widget 37).
- 2 Step 2: A potential problem: if there is a cyclical pattern in the production process (e.g., every 100th widget comes from the same machine position), the sample could be biased. Systematic sampling assumes no periodicity in the population.
Answer
This is systematic sampling. A potential problem is that if the production process has a cycle of exactly 100 (or a factor of 100), the sample could consistently capture the same type of defect or miss it entirely.
Systematic sampling is efficient for production lines and large ordered populations, but it assumes no periodic patterns in the data. If the sampling interval aligns with a production cycle, the sample may not be representative.
About Random Sampling
Random sampling is a method of selecting individuals from a population where every member has an equal chance of being chosen, ensuring the sample is unbiased and representative of the whole population.
Learn more about Random Sampling →More Random Sampling Examples
Example 1 easy
A school has 500 students numbered 001–500. Describe how to select a simple random sample of 20 stud
Example 2 mediumExplain the difference between simple random sampling, stratified sampling, and systematic sampling.
Example 4 hardA university has 12,000 students: 7,200 undergraduates and 4,800 postgraduates. A researcher wants a