Poisson regression relates a count outcome (defects, accidents, events) to a predictor. Model: log(E[Y]) = β₀ + β₁X. One observation per line; separate X and Y with a space, tab or comma.

Kaplan-Meier estimates the survival function from time-to-event data. Enter survival time and event status (1 = event occurred / failed, 0 = censored / still running). One subject per line; separate time and status with a space, tab or comma.

The chi-square goodness-of-fit test checks whether observed counts follow a Poisson distribution. Enter the observed frequency table, one count:frequency pair per line. Expected frequencies are computed from the fitted λ, groups with expected frequency < 5 are pooled, and the p-value is reported.