Explanation 1
Convenience data is fast but can miss quieter groups.
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Lesson 8 of 12
Evaluate judgment, convenience, focus group, POS, loyalty, and web analytics data with a bias-aware lens.
Theory
Non-random data can be useful for exploration, operations, and early signals, but it rarely supports broad claims without caution. Judgment samples rely on expert selection. Convenience samples use easy-to-reach units. Focus groups provide depth, while point-of-sale, loyalty, and web data provide behavioral traces with coverage limits.
Explanation 1
Convenience data is fast but can miss quieter groups.
Explanation 2
Focus groups are rich but not representative by default.
Explanation 3
Web analytics measures visible behavior, not every learner experience.
Interactive Mission
A survey is sent to 2,000 learners, but only the most active 80 reply.
A college survey excludes part-time online students from the email list.
A question asks, 'How excellent was the new platform?'
Study hours are recorded in minutes for some learners and hours for others.
Diagnoses matched: 0/4
Worked example
Scenario
A platform compares feedback from learners who clicked a popup with a planned random sample from active accounts.
Convenience can help discover issues, but representative claims need stronger design.
R connection
Use repeated samples to see how sample-based summaries vary.
Live R Lab
Use repeated samples to show how sample means vary around a population mean.
Ready to run
Assistant
Help me evaluate whether a business data source is fast, biased, useful, or unsuitable for a claim.
Exit check
Use the hint button if you need coaching before answering. Explanations appear after you check or submit.
Checkpoint
Question 1 of 2. Answered 0/2. Passing score: 70%.