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Visual Guides/Sampling Methods & Bias
STATISTICS & SAMPLING

Sampling Methods & Bias

Simulate random, stratified, cluster, and systematic sampling on a population of 1,000 units. See how well each method estimates the true mean, and why convenience sampling leads to disaster. Backed by famous real-world failures.

Methods tried: 1/3
Sample size adjusted
Repeated draws: 0/10
Bias gallery viewed

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Population (N = 1000)

Mean = 63.20 SD = 12.76

Group A (600, 60%)
Group B (400, 40%)

Sampling Method

Sample Size

n = 100
10100200

Larger samples tend to be more representative. Adjust to see the effect.

Draw Samples

“Draw 10 More” and “Draw 100 More” add repeated draws to the distribution chart below, great for seeing sampling variability.

Results Comparison

Draw a sample to see results here.

Repeated Draws Distribution

Draw samples to populate this chart.

True μ455055606570758085

Each dot = one sample mean. The spread of dots shows sampling variability (precision). A good method needs both a small spread AND dots centered on the true mean (low bias). A tight cluster in the wrong place is precisely wrong: try the convenience method to see it. The red dashed line marks the true population mean.

Methods Tried

RandomStratifiedClusterSystematicConvenience

Try all 5 methods and compare how each estimates the population mean.

← Sources of BiasConfidence Intervals →