Poisson Rate Test
Analyse PhaseGBTest whether an observed defect/event rate differs significantly from a target (one-sample) or from another process (two-sample). Uses exact Poisson probability for one-sample and score test for two-sample.
H₀: Observed rate = Target rate. H₁: Observed rate ≠ Target rate (two-tailed exact test).
Observed rate is significantly different from target (p < 0.05)
Observed Rate
0.047000
Target Rate
0.040000
p-value
0.000000
Significant?
Yes (p < 0.05)
Rate 95% CI Low
0.035313
Rate 95% CI High
0.062555
p (less)
0.880417
p (greater)
0.000000
One-Sample Poisson Test
Use when you have a count of events over a time period or number of units, and want to compare to a known or target rate. Examples: defect counts per shift, hospital readmissions per 1000 patients, machine failures per month.
Two-Sample Poisson Test
Use when comparing defect rates between two processes, time periods, or machines. The test accounts for different observation windows (time or units). Example: Line A had 47 defects in 1000 units vs Line B had 62 defects in 1200 units.