How to Use Statsmodels for Regression Analysis in Catalysis?
One of the primary uses of Statsmodels in catalysis research is regression analysis. Researchers can use regression models to understand how different variables affect catalytic activity. For example, you can use a linear regression model to investigate the relationship between temperature and reaction rate. Here is a simple example of how to implement a linear regression model using Statsmodels:
import statsmodels.api as sm import pandas as pd
# Assume 'data' is a DataFrame containing your experimental data X = data[['temperature', 'pressure']] Y = data['reaction_rate']
# Adding a constant to the model (intercept) X = sm.add_constant(X)
# Fitting the model model = sm.OLS(Y, X).fit()
# Getting the summary of the model print(model.summary())
