Get startedGet started for free

Statistical significance

In the video we analyzed the horseshoe crab model by predicting y with weight. In this exercise you will assess the significance of the estimated coefficients but with width as explanatory variable instead.

Recall that coefficients help us determine the significance of the relationship that we are trying to model, where a positive sign increases the probability of an event as the predictor increases and vice versa.

The dataset crab is loaded in the workspace.

This exercise is part of the course

Generalized Linear Models in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import libraries and th glm function
import ____.api as sm
from ____.____.api import ____

# Fit logistic regression and save as crab_GLM
crab_GLM = ____('____ ~ ____', data = ____, family = sm.families.____).____

# Print model summary
____(____.____)
Edit and Run Code