Regression table – P-value for Probit Analysis

Probit regression examines the relationship between a binomial response and a continuous stress predictor variable. To determine whether or not the stressor has a statistically significant impact on the outcome (survival or failure) of your unit you need to do the following:
  • Identify the p-value for Stress, which is the second value under P.
  • Compare the p-value to your α-level: If the p-value is smaller than the α-level you have selected, the relationship between the response outcome and stress variable is statistically significantly.

A commonly used α-level is 0.05.

Example output

Regression Table Standard Variable Coef Error Z P Constant -6.20376 1.06565 -5.82 0.000 Stress 0.0089596 0.0015615 5.74 0.000 Natural Response 0 Log-Likelihood = -38.516

Interpretation

For the windshield data, the p-value for Stress is 0.000, which is smaller than 0.05, indicating that the velocity of the projectile does have a significant impact on whether or not the windshield breaks.

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