Explanation 1
With replacement: a unit can be selected more than once.
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Lesson 7 of 12
Compare simple random, systematic, stratified, and cluster sampling designs for finite populations.
Theory
Random sampling gives units a known selection process. Simple random sampling selects units directly. Systematic sampling uses a fixed interval after a start. Stratified sampling samples within important groups. Cluster sampling selects whole groups when individual selection is costly.
Explanation 1
With replacement: a unit can be selected more than once.
Explanation 2
Without replacement: each selected unit appears once.
Explanation 3
Finite population: the frame has a limited number of units.
Interactive Mission
R connection
Practice sample(), replacement choices, and seq() on a student frame.
Live R Lab
Use set.seed(), sample(), replacement choices, and seq() to create reproducible samples from a frame.
Ready to run
R connection
Use dplyr group_by() and slice_sample() to sample within program groups.
Live R Lab
Use dplyr to sample within groups and compare sample composition with the full frame.
Ready to run
Assistant
Compare simple random, systematic, stratified, and cluster sampling for a scenario I describe, without giving quiz answers.
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%.